experiment: complete xiiotid three-alpha beta study
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dataset,alpha,seed,same_manifest_content_hash,round0_snapshot_sha256_original,round0_snapshot_sha256_beta0,round0_snapshot_byte_identical,support_char_rare_identical,aggregation_max_abs_diff,history_rare_f1_round0_diff,history_rare_f1_max_diff_rounds_ge1,test_metric_max_abs_diff,classification
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xiiotid,0.75,0,True,8c477df6b3af645bf2db1c8005d86ea6258b283370ff3ef3e6e88d6f40095564,8c477df6b3af645bf2db1c8005d86ea6258b283370ff3ef3e6e88d6f40095564,True,True,4.440892098500626e-16,0.0,0.011009861120389763,0.004327580965537758,B
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xiiotid,0.75,1,True,41f0187c4f0a8e3db0a8ab7eff0aa50a8f3e4a64ded2448228bd133ea017869d,41f0187c4f0a8e3db0a8ab7eff0aa50a8f3e4a64ded2448228bd133ea017869d,True,True,4.440892098500626e-16,0.0,0.008121999469173913,0.0011361472938199446,B
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xiiotid,0.75,2,True,be2ad5fb5fcf87c49b2826936c8d5dae6cdc4ab25fe2677081acec32f8116648,be2ad5fb5fcf87c49b2826936c8d5dae6cdc4ab25fe2677081acec32f8116648,True,True,2.220446049250313e-16,0.0,0.0036395109195792585,0.0008478378239292761,B
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||||
0,0.75,7,11,0.5066197183098592,0.7475490196078431,0.003753943217665645
|
||||
0,0.75,8,5,0.254476137884162,0.9258064516129032,-0.012133568199228284
|
||||
0,0.75,9,33,0.5747027822037014,0.9321428571428572,-0.04332234195639206
|
||||
0,1.0,0,85,0.41037735849056606,0.6695652173913043,0.02220072031392789
|
||||
0,1.0,1,95,0.4364963503649635,0.6598684210526315,-0.01594744240140994
|
||||
0,1.0,2,30,0.8104575163398693,0.7515151515151515,-0.023418705158502084
|
||||
0,1.0,3,1,0.3872624550590652,0.6532258064516129,-0.007253919655329344
|
||||
0,1.0,4,27,0.5075591973506813,0.7899560117302054,-0.0011161946435505055
|
||||
0,1.0,5,30,0.31395372458203835,0.5892857142857143,-0.010525161498107505
|
||||
0,1.0,6,111,0.6330128205128205,0.9038461538461539,-0.04534975258659468
|
||||
0,1.0,7,11,0.4982974910394265,0.7475490196078431,-0.0045682840527670465
|
||||
0,1.0,8,5,0.24104813726132104,0.9258064516129032,-0.025561568822069253
|
||||
0,1.0,9,33,0.5529953917050692,0.9321428571428572,-0.0650297324550243
|
||||
1,0.0,0,8,0.7317073170731707,0.7894736842105263,0.0
|
||||
1,0.0,1,39,0.45412527593818985,0.9240506329113924,0.0
|
||||
1,0.0,2,114,0.0,0.0,0.0
|
||||
1,0.0,3,22,0.41601055113704494,0.7105263157894737,0.0
|
||||
1,0.0,4,116,0.5073271413828689,0.976027397260274,0.0
|
||||
1,0.0,5,194,0.4969913891482519,0.8181818181818181,0.0
|
||||
1,0.0,6,11,0.4932603628255802,0.7532679738562091,0.0
|
||||
1,0.0,7,80,0.4712393272262289,0.742,0.0
|
||||
1,0.0,8,75,0.3824713298397509,0.967741935483871,0.0
|
||||
1,0.0,9,4,0.12962264150943395,0.8653846153846154,0.0
|
||||
1,0.25,0,8,0.7500000000000001,0.7894736842105263,0.018292682926829396
|
||||
1,0.25,1,39,0.4631260849996785,0.9240506329113924,0.009000809061488646
|
||||
1,0.25,2,114,0.0,0.0,0.0
|
||||
1,0.25,3,22,0.4282644089873005,0.7052631578947368,0.012253857850255567
|
||||
1,0.25,4,116,0.512109542148053,0.976027397260274,0.004782400765184103
|
||||
1,0.25,5,194,0.5046143250688705,0.8181818181818181,0.007622935920618579
|
||||
1,0.25,6,11,0.5138888888888888,0.6977124183006536,0.020628526063308616
|
||||
1,0.25,7,80,0.4785636378890847,0.742,0.007324310662855771
|
||||
1,0.25,8,75,0.4018918918918919,0.967741935483871,0.01942056205214099
|
||||
1,0.25,9,4,0.16140159767610748,0.8653846153846154,0.03177895616667353
|
||||
1,0.5,0,8,0.7500000000000001,0.7894736842105263,0.018292682926829396
|
||||
1,0.5,1,39,0.4631260849996785,0.9240506329113924,0.009000809061488646
|
||||
1,0.5,2,114,0.0,0.0,0.0
|
||||
1,0.5,3,22,0.42720530835284937,0.7,0.01119475721580443
|
||||
1,0.5,4,116,0.5109751121991024,0.976027397260274,0.00364797081623347
|
||||
1,0.5,5,194,0.5041322314049587,0.8181818181818181,0.0071408422567067475
|
||||
1,0.5,6,11,0.5153949129852744,0.6977124183006536,0.022134550159694177
|
||||
1,0.5,7,80,0.4752563659407765,0.742,0.004017038714547616
|
||||
1,0.5,8,75,0.41330409356725145,0.967741935483871,0.030832763727500545
|
||||
1,0.5,9,4,0.1697948717948718,0.8653846153846154,0.04017223028543784
|
||||
1,0.75,0,8,0.7692307692307692,0.7894736842105263,0.03752345215759845
|
||||
1,0.75,1,39,0.4558730158730159,0.9177215189873418,0.0017477399348260203
|
||||
1,0.75,2,114,0.0,0.0,0.0
|
||||
1,0.75,3,22,0.4263857077416399,0.7052631578947368,0.010375156604594982
|
||||
1,0.75,4,116,0.5097250167672703,0.9726027397260274,0.0023978753844013934
|
||||
1,0.75,5,194,0.49891257068290557,0.8181818181818181,0.0019211815346536487
|
||||
1,0.75,6,11,0.5031746031746032,0.6830065359477124,0.00991424034902294
|
||||
1,0.75,7,80,0.47631496392345496,0.742,0.005075636697226049
|
||||
1,0.75,8,75,0.40862068965517245,0.9516129032258065,0.026149359815421547
|
||||
1,0.75,9,4,0.16229274743159391,0.8653846153846154,0.032670105922159964
|
||||
1,1.0,0,8,0.7894736842105263,0.7894736842105263,0.05776636713735561
|
||||
1,1.0,1,39,0.46126520681265204,0.9240506329113924,0.007139930874462186
|
||||
1,1.0,2,114,0.0,0.0,0.0
|
||||
1,1.0,3,22,0.4258008807529574,0.7052631578947368,0.009790329615912474
|
||||
1,1.0,4,116,0.5109154929577465,0.9726027397260274,0.0035883515748775796
|
||||
1,1.0,5,194,0.4932608575073492,0.8181818181818181,-0.003730531640902701
|
||||
1,1.0,6,11,0.49415204678362573,0.6830065359477124,0.0008916839580455083
|
||||
1,1.0,7,80,0.45961850649350655,0.714,-0.011620820732722359
|
||||
1,1.0,8,75,0.40796812749003986,0.9516129032258065,0.02549679765028895
|
||||
1,1.0,9,4,0.1528863293569176,0.8653846153846154,0.023263687847483644
|
||||
2,0.0,0,28,0.3908297845950303,0.6323529411764706,0.0
|
||||
2,0.0,1,39,0.6375000000000001,0.9444444444444444,0.0
|
||||
2,0.0,2,1,0.7719499452047811,0.9395936724565757,0.0
|
||||
2,0.0,3,25,0.5140740740740741,0.7261904761904762,0.0
|
||||
2,0.0,4,17,0.32665945165945165,0.9261363636363636,0.0
|
||||
2,0.0,5,1,0.48815593666902485,0.7137486573576799,0.0
|
||||
2,0.0,6,11,0.08212058212058213,0.875,0.0
|
||||
2,0.0,7,3,0.7083882301273605,0.861965811965812,0.0
|
||||
2,0.0,8,28,0.6666666666666667,0.9,0.0
|
||||
2,0.0,9,22,0.5140402843601896,0.8813559322033898,0.0
|
||||
2,0.25,0,28,0.3674622674622674,0.6470588235294117,-0.023367517132762916
|
||||
2,0.25,1,39,0.6756756756756757,0.9259259259259259,0.03817567567567559
|
||||
2,0.25,2,1,0.7817933138693811,0.9347859801488834,0.009843368664600005
|
||||
2,0.25,3,25,0.516448326055313,0.7420634920634921,0.002374251981238862
|
||||
2,0.25,4,17,0.33892890698402756,0.9147727272727273,0.012269455324575906
|
||||
2,0.25,5,1,0.49178148139657507,0.723952738990333,0.003625544727550223
|
||||
2,0.25,6,11,0.08400537634408603,0.875,0.001884794223503905
|
||||
2,0.25,7,3,0.7063492063492063,0.8581196581196582,-0.0020390237781542364
|
||||
2,0.25,8,28,0.5454545454545454,0.9,-0.12121212121212133
|
||||
2,0.25,9,22,0.5403669724770642,0.9067796610169492,0.026326688116874664
|
||||
2,0.5,0,28,0.35769624791906773,0.6470588235294117,-0.03313353667596258
|
||||
2,0.5,1,39,0.6853146853146853,0.9074074074074074,0.047814685314685246
|
||||
2,0.5,2,1,0.7969336932023707,0.9299782878411911,0.024983747997589623
|
||||
2,0.5,3,25,0.5212121212121212,0.75,0.00713804713804711
|
||||
2,0.5,4,17,0.32757919209532116,0.9034090909090908,0.0009197404358695094
|
||||
2,0.5,5,1,0.49211376858435685,0.7290547798066596,0.003957831915332
|
||||
2,0.5,6,11,0.08058905380333951,0.875,-0.0015315283172426114
|
||||
2,0.5,7,3,0.7028769841269842,0.8581196581196582,-0.005511246000376335
|
||||
2,0.5,8,28,0.5142857142857143,0.9,-0.1523809523809524
|
||||
2,0.5,9,22,0.5508168961083759,0.9279661016949152,0.03677661174818636
|
||||
2,0.75,0,28,0.3623640661938534,0.6470588235294117,-0.028465718401176898
|
||||
2,0.75,1,39,0.6906474820143885,0.8888888888888888,0.05314748201438846
|
||||
2,0.75,2,1,0.808444546709618,0.9275744416873448,0.036494601504836854
|
||||
2,0.75,3,25,0.518840579710145,0.746031746031746,0.004766505636070839
|
||||
2,0.75,4,17,0.31875000000000003,0.9034090909090908,-0.007909451659451616
|
||||
2,0.75,5,1,0.4892330447644321,0.723952738990333,0.001077108095407231
|
||||
2,0.75,6,11,0.07973967176004527,0.875,-0.0023809103605368503
|
||||
2,0.75,7,3,0.7063492063492063,0.8581196581196582,-0.0020390237781542364
|
||||
2,0.75,8,28,0.5806451612903225,0.9,-0.08602150537634423
|
||||
2,0.75,9,22,0.5420062695924766,0.9152542372881356,0.027965985232286994
|
||||
2,1.0,0,28,0.35290668699246575,0.6470588235294117,-0.03792309760256457
|
||||
2,1.0,1,39,0.6906474820143885,0.8888888888888888,0.05314748201438846
|
||||
2,1.0,2,1,0.8155581947743469,0.9227667493796525,0.04360824956956577
|
||||
2,1.0,3,25,0.5243128964059196,0.75,0.010238822331845476
|
||||
2,1.0,4,17,0.31250962476258914,0.9034090909090908,-0.014149826896862505
|
||||
2,1.0,5,1,0.49042145593869735,0.723952738990333,0.0022655192696725
|
||||
2,1.0,6,11,0.08345397084310327,0.875,0.001333388722521145
|
||||
2,1.0,7,3,0.7063492063492063,0.8581196581196582,-0.0020390237781542364
|
||||
2,1.0,8,28,0.5454545454545454,0.9,-0.12121212121212133
|
||||
2,1.0,9,22,0.5497412305922944,0.923728813559322,0.035700946232104847
|
||||
|
@@ -0,0 +1,16 @@
|
||||
seed,beta,n_eligible,n_improve_vs_beta0,n_degrade_vs_beta0,n_unchanged,mean_delta_vs_beta0,median_delta_vs_beta0,min_delta_vs_beta0,max_delta_vs_beta0
|
||||
0,0.0,10,0,0,10,0.0,0.0,0.0,0.0
|
||||
0,0.25,10,5,5,0,8.859496571733683e-05,-0.001404275185996784,-0.019237420306723707,0.026871905512682204
|
||||
0,0.5,10,6,4,0,0.007584665753678871,0.013188342258148383,-0.0361435910590483,0.048012173012172976
|
||||
0,0.75,10,3,7,0,-0.009935209564988324,-0.010284597102047655,-0.04332234195639206,0.02528490028490027
|
||||
0,1.0,10,1,9,0,-0.017657004095942678,-0.013236301949758722,-0.0650297324550243,0.02220072031392789
|
||||
1,0.0,10,0,0,10,0.0,0.0,0.0,0.0
|
||||
1,0.25,10,9,0,1,0.01311050414693552,0.010627333455872107,0.0,0.03177895616667353
|
||||
1,0.5,10,9,0,1,0.014643364516424288,0.010097783138646538,0.0,0.04017223028543784
|
||||
1,0.75,10,9,0,1,0.0127774748399905,0.007494938523124495,0.0,0.03752345215759845
|
||||
1,1.0,10,7,2,1,0.011258579628480089,0.005364141224669883,-0.011620820732722359,0.05776636713735561
|
||||
2,0.0,10,0,0,10,0.0,0.0,0.0,0.0
|
||||
2,0.25,10,7,3,0,-0.005211888340901932,0.0029998983543945423,-0.12121212121212133,0.03817567567567559
|
||||
2,0.5,10,6,4,0,-0.007096659882482407,0.0024387861756007545,-0.1523809523809524,0.047814685314685246
|
||||
2,0.75,10,5,5,0,-0.00033649270926734557,-0.0004809578413735027,-0.08602150537634423,0.05314748201438846
|
||||
2,1.0,10,6,4,0,-0.002902966134960444,0.0017994539960968226,-0.12121212121212133,0.05314748201438846
|
||||
|
@@ -0,0 +1,46 @@
|
||||
class_id,class_name,beta,n_seeds,n_contributors_seed0,mean_displacement,std_sample_displacement,min_displacement,max_displacement,mean_relative_displacement
|
||||
0,C&C,0.0,3,8,0.0,0.0,0.0,0.0,0.0
|
||||
0,C&C,0.25,3,8,0.439241829432576,0.2482668440171278,0.1577100781963558,0.6268193555516579,0.08997758594748201
|
||||
0,C&C,0.5,3,8,0.7678410072672376,0.3909965913837135,0.3264883941700919,1.0708837976422039,0.15701946966810795
|
||||
0,C&C,0.75,3,8,1.0410848664700902,0.4814392749891062,0.503350519095841,1.4320794500312022,0.21255529764935774
|
||||
0,C&C,1.0,3,8,1.2839465030740465,0.5431989970423492,0.6847690195463256,1.7441743055076424,0.2617816727650299
|
||||
1,Exfiltration,0.0,3,10,0.0,0.0,0.0,0.0,0.0
|
||||
1,Exfiltration,0.25,3,10,0.6096329492397241,0.15529587518313812,0.4303188395756118,0.7005731273791159,0.08815738333426759
|
||||
1,Exfiltration,0.5,3,10,0.9900899725245896,0.15059193858817135,0.8191503402527969,1.1031761525926143,0.1423829525956932
|
||||
1,Exfiltration,0.75,3,10,1.2536544998955659,0.10576760245352612,1.1487441777538223,1.3602590280897369,0.17957488577930802
|
||||
1,Exfiltration,1.0,3,10,1.4475761921343262,0.08598433748869257,1.3846272466974707,1.545544115617925,0.20679504552799255
|
||||
2,Exploitation,0.0,3,9,0.0,0.0,0.0,0.0,0.0
|
||||
2,Exploitation,0.25,3,9,0.4576570034781726,0.128934732252835,0.33213289764322984,0.5897511508531448,0.08525019886525016
|
||||
2,Exploitation,0.5,3,9,0.8504289045197803,0.09539544332992135,0.7494922500463251,0.93909585013325,0.15761005429469221
|
||||
2,Exploitation,0.75,3,9,1.2085539298827332,0.04564296145945021,1.1636103575185945,1.2548655232819537,0.22330324296750917
|
||||
2,Exploitation,1.0,3,9,1.5392602070293495,0.25171201225922846,1.321824115607462,1.8150114731665588,0.2839417733897609
|
||||
3,Lateral_movement,0.0,3,10,0.0,0.0,0.0,0.0,0.0
|
||||
3,Lateral_movement,0.25,3,10,0.5461495626298819,0.3229980967371187,0.2574665523313587,0.8950011168465136,0.10516299618218877
|
||||
3,Lateral_movement,0.5,3,10,0.9115139836526881,0.4493586574794453,0.47846985675017045,1.3755795607902412,0.1749147577856791
|
||||
3,Lateral_movement,0.75,3,10,1.1750905945007586,0.5128745337831714,0.6579842973620211,1.6836259334315673,0.22498947669980307
|
||||
3,Lateral_movement,1.0,3,10,1.3693216274264168,0.5527158531960167,0.7972700943677291,1.9004241105530428,0.2618053240393338
|
||||
4,Normal,0.0,3,10,0.0,0.0,0.0,0.0,0.0
|
||||
4,Normal,0.25,3,10,0.3154682998030463,0.10443504134088931,0.24171855410307602,0.43497131021382573,0.056799260146204594
|
||||
4,Normal,0.5,3,10,0.5587470690472488,0.17823349266094118,0.45369233971395007,0.7645382774267853,0.10039903187569306
|
||||
4,Normal,0.75,3,10,0.7490874520257846,0.23967850866469875,0.5824041031282855,1.023762039001287,0.13441982891499835
|
||||
4,Normal,1.0,3,10,0.9031246281714095,0.298425213658255,0.6776684342907874,1.241539979132905,0.1619501084487235
|
||||
5,RDOS,0.0,3,10,0.0,0.0,0.0,0.0,0.0
|
||||
5,RDOS,0.25,3,10,0.3650484364726993,0.08772907886913217,0.2637502192596181,0.4163257737915561,0.04288134985761141
|
||||
5,RDOS,0.5,3,10,0.5879547998772782,0.1377057429524652,0.4316771118028957,0.6915069239012192,0.06911307720839648
|
||||
5,RDOS,0.75,3,10,0.7227236354412905,0.1717679379909637,0.5354842605581158,0.8730027165584727,0.08499831650437539
|
||||
5,RDOS,1.0,3,10,0.8141011244781585,0.20007357231332454,0.6016395266536176,0.9989098237543187,0.0957646213985643
|
||||
6,Reconnaissance,0.0,3,10,0.0,0.0,0.0,0.0,0.0
|
||||
6,Reconnaissance,0.25,3,10,0.3538777272136799,0.16940535581118332,0.2038596395428698,0.5376024764747891,0.06147155478185134
|
||||
6,Reconnaissance,0.5,3,10,0.6312092223602926,0.29492004860244364,0.3788239457941236,0.9554020858885306,0.10971563529074672
|
||||
6,Reconnaissance,0.75,3,10,0.8356476563748476,0.37207240085585064,0.5243911576151126,1.2477469868993738,0.14524085580982543
|
||||
6,Reconnaissance,1.0,3,10,0.9825580428619212,0.4118545897797079,0.6421335927154392,1.4403595556867412,0.17068982082838355
|
||||
7,Tampering,0.0,3,10,0.0,0.0,0.0,0.0,0.0
|
||||
7,Tampering,0.25,3,10,0.6563816910351933,0.2744029329153262,0.4954736962043322,0.9732218819818169,0.13525459838255058
|
||||
7,Tampering,0.5,3,10,1.1965659871259866,0.40237474952297886,0.9327814268885475,1.6596964268654473,0.24630572605937992
|
||||
7,Tampering,0.75,3,10,1.6159352389599746,0.43450150845394425,1.2965161502244944,2.110712157391946,0.33220594130333053
|
||||
7,Tampering,1.0,3,10,1.934147031540858,0.4266139988379522,1.6015145240420323,2.4151317063636144,0.397088566305455
|
||||
8,Weaponization,0.0,3,10,0.0,0.0,0.0,0.0,0.0
|
||||
8,Weaponization,0.25,3,10,0.551565983863633,0.1338613313384844,0.47266743210924217,0.7061244249971462,0.08855674634387566
|
||||
8,Weaponization,0.5,3,10,0.97107833710167,0.1924628955103443,0.8478196060028891,1.1928558529811986,0.1557172379213153
|
||||
8,Weaponization,0.75,3,10,1.2674609635647072,0.19324637928770602,1.121875452958101,1.4867044185381322,0.2029649148872006
|
||||
8,Weaponization,1.0,3,10,1.4719590343511655,0.17030548300304388,1.3197795639990293,1.6559144922727265,0.23542365279592728
|
||||
|
@@ -0,0 +1,19 @@
|
||||
dataset,alpha,seed,aggregation,wall_clock,wall_seconds,cpu_percent,peak_rss_kb,peak_rss_gib,swaps
|
||||
xiiotid,0.75,0,original_protean,40:40.74,2440.74,745,6802212,6.487,0
|
||||
xiiotid,0.75,0,support_weighted_beta0,40:04.93,2404.93,746,6802620,6.487,0
|
||||
xiiotid,0.75,0,support_weighted_beta0.25,40:50.34,2450.34,745,6802460,6.487,0
|
||||
xiiotid,0.75,0,support_weighted_beta0.5,40:48.88,2448.88,746,6802324,6.487,0
|
||||
xiiotid,0.75,0,support_weighted_beta0.75,40:48.60,2448.6,746,6802508,6.487,0
|
||||
xiiotid,0.75,0,support_weighted_beta1,40:09.82,2409.82,745,6802340,6.487,0
|
||||
xiiotid,0.75,1,original_protean,40:25.70,2425.7,745,7246836,6.911,0
|
||||
xiiotid,0.75,1,support_weighted_beta0,40:00.25,2400.25,745,7246820,6.911,0
|
||||
xiiotid,0.75,1,support_weighted_beta0.25,40:10.91,2410.91,745,7246508,6.911,0
|
||||
xiiotid,0.75,1,support_weighted_beta0.5,40:16.31,2416.31,745,7246668,6.911,0
|
||||
xiiotid,0.75,1,support_weighted_beta0.75,40:18.58,2418.58,744,7246868,6.911,0
|
||||
xiiotid,0.75,1,support_weighted_beta1,49:01.62,2941.62,714,7247000,6.911,0
|
||||
xiiotid,0.75,2,original_protean,40:18.15,2418.15,745,7550444,7.201,0
|
||||
xiiotid,0.75,2,support_weighted_beta0,40:31.08,2431.08,745,7550036,7.2,0
|
||||
xiiotid,0.75,2,support_weighted_beta0.25,40:18.53,2418.53,745,7549860,7.2,0
|
||||
xiiotid,0.75,2,support_weighted_beta0.5,43:17.28,2597.28,732,7549856,7.2,0
|
||||
xiiotid,0.75,2,support_weighted_beta0.75,41:01.74,2461.74,744,7549924,7.2,0
|
||||
xiiotid,0.75,2,support_weighted_beta1,40:27.57,2427.57,745,7550556,7.201,0
|
||||
|
@@ -0,0 +1,111 @@
|
||||
{
|
||||
"alpha": 0.75,
|
||||
"betas": [
|
||||
0.0,
|
||||
0.25,
|
||||
0.5,
|
||||
0.75,
|
||||
1.0
|
||||
],
|
||||
"dataset": "xiiotid",
|
||||
"missing_artifacts": [],
|
||||
"n_missing_artifacts": 0,
|
||||
"outputs": {
|
||||
"client_deltas": "/home/willtanoe/projects/perdalam-protean/artifacts/analysis/xiiotid__alpha0.75__multiseed__client_validation_deltas.csv",
|
||||
"client_validation_detail": "/home/willtanoe/projects/perdalam-protean/artifacts/analysis/xiiotid__alpha0.75__multiseed__client_validation_detail.csv",
|
||||
"client_validation_summary": "/home/willtanoe/projects/perdalam-protean/artifacts/analysis/xiiotid__alpha0.75__multiseed__client_validation_summary.csv",
|
||||
"per_seed": "/home/willtanoe/projects/perdalam-protean/artifacts/analysis/xiiotid__alpha0.75__multiseed__validation_per_seed.csv",
|
||||
"pooled": "/home/willtanoe/projects/perdalam-protean/artifacts/analysis/xiiotid__alpha0.75__multiseed__validation_pooled.csv",
|
||||
"prototype_effect_pooled": "/home/willtanoe/projects/perdalam-protean/artifacts/analysis/xiiotid__alpha0.75__multiseed__prototype_effect_pooled.csv",
|
||||
"test_descriptive": "/home/willtanoe/projects/perdalam-protean/artifacts/analysis/xiiotid__alpha0.75__multiseed__test_descriptive.csv"
|
||||
},
|
||||
"per_seed_diagnostic": [
|
||||
{
|
||||
"seed": 0,
|
||||
"selected_beta": 0.5,
|
||||
"test_used_for_selection": false,
|
||||
"val_rare_macro_f1_per_client_mean": 0.5043877141202036
|
||||
},
|
||||
{
|
||||
"seed": 1,
|
||||
"selected_beta": 0.5,
|
||||
"test_used_for_selection": false,
|
||||
"val_rare_macro_f1_per_client_mean": 0.42291889812447636
|
||||
},
|
||||
{
|
||||
"seed": 2,
|
||||
"selected_beta": 0.0,
|
||||
"test_used_for_selection": false,
|
||||
"val_rare_macro_f1_per_client_mean": 0.5100384955477162
|
||||
}
|
||||
],
|
||||
"pooled_table": [
|
||||
{
|
||||
"beta": 0.0,
|
||||
"max_val_rare_macro_f1": 0.5100384955477162,
|
||||
"min_val_rare_macro_f1": 0.408275533608052,
|
||||
"n_seeds": 3,
|
||||
"pooled_val_rare_macro_f1_per_client_mean": 0.471705692507431,
|
||||
"pooled_val_rare_recall_global": 0.8703636412250875,
|
||||
"pooled_val_rare_recall_per_client_mean": 0.7872893964865675,
|
||||
"std_pop_val_rare_macro_f1": 0.04517619623224806,
|
||||
"std_sample_val_rare_macro_f1": 0.055329314644425844
|
||||
},
|
||||
{
|
||||
"beta": 0.25,
|
||||
"max_val_rare_macro_f1": 0.5048266072068142,
|
||||
"min_val_rare_macro_f1": 0.4213860377549875,
|
||||
"n_seeds": 3,
|
||||
"pooled_val_rare_macro_f1_per_client_mean": 0.47436809609801456,
|
||||
"pooled_val_rare_recall_global": 0.8659485773851721,
|
||||
"pooled_val_rare_recall_per_client_mean": 0.7842747460964024,
|
||||
"std_pop_val_rare_macro_f1": 0.037603765703456124,
|
||||
"std_sample_val_rare_macro_f1": 0.04605501919031881
|
||||
},
|
||||
{
|
||||
"beta": 0.5,
|
||||
"max_val_rare_macro_f1": 0.5043877141202036,
|
||||
"min_val_rare_macro_f1": 0.42291889812447636,
|
||||
"n_seeds": 3,
|
||||
"pooled_val_rare_macro_f1_per_client_mean": 0.47674948263663786,
|
||||
"pooled_val_rare_recall_global": 0.8625873633552743,
|
||||
"pooled_val_rare_recall_per_client_mean": 0.7865311249627326,
|
||||
"std_pop_val_rare_macro_f1": 0.038068547934984834,
|
||||
"std_sample_val_rare_macro_f1": 0.04662425884469754
|
||||
},
|
||||
{
|
||||
"beta": 0.75,
|
||||
"max_val_rare_macro_f1": 0.5097020028384487,
|
||||
"min_val_rare_macro_f1": 0.42105300844804255,
|
||||
"n_seeds": 3,
|
||||
"pooled_val_rare_macro_f1_per_client_mean": 0.47254095002934254,
|
||||
"pooled_val_rare_recall_global": 0.8571058191363848,
|
||||
"pooled_val_rare_recall_per_client_mean": 0.7807290076221336,
|
||||
"std_pop_val_rare_macro_f1": 0.03758196249998729,
|
||||
"std_sample_val_rare_macro_f1": 0.04602831582869046
|
||||
},
|
||||
{
|
||||
"beta": 1.0,
|
||||
"max_val_rare_macro_f1": 0.5071355294127556,
|
||||
"min_val_rare_macro_f1": 0.4195341132365321,
|
||||
"n_seeds": 3,
|
||||
"pooled_val_rare_macro_f1_per_client_mean": 0.46860522897329,
|
||||
"pooled_val_rare_recall_global": 0.8580493104245459,
|
||||
"pooled_val_rare_recall_per_client_mean": 0.7813087218498457,
|
||||
"std_pop_val_rare_macro_f1": 0.0365315719104147,
|
||||
"std_sample_val_rare_macro_f1": 0.044741855341153436
|
||||
}
|
||||
],
|
||||
"primary_selection": {
|
||||
"rule": "max pooled validation per-client-mean rare-class macro-F1 (tie-break: recall, then lower std, then smaller beta)",
|
||||
"selected_beta": 0.5,
|
||||
"selection_split": "validation",
|
||||
"test_used_for_selection": false,
|
||||
"tie_break_used": false
|
||||
},
|
||||
"seeds": [
|
||||
0,
|
||||
1,
|
||||
2
|
||||
]
|
||||
}
|
||||
@@ -0,0 +1,19 @@
|
||||
seed,aggregation,beta,test_rare_macro_f1,test_rare_recall,test_macro_f1,test_accuracy,test_weighted_f1,test_rare_support
|
||||
0,support_weighted_beta0,0.0,0.5258677063515844,0.8189572858633267,0.7443730765700634,0.9137449257205323,0.932603306821729,6251
|
||||
0,support_weighted_beta0.25,0.25,0.5208517449565646,0.8112672838772567,0.7451504229744649,0.9151390091567331,0.9352837167180253,6251
|
||||
0,support_weighted_beta0.5,0.5,0.5118888965076885,0.8038871133887995,0.741976732126316,0.9143652007295908,0.9355656459425888,6251
|
||||
0,support_weighted_beta0.75,0.75,0.5023100771543629,0.7958803441208939,0.7364315054618653,0.9122771462436514,0.9343191013066571,6251
|
||||
0,support_weighted_beta1,1.0,0.5060638094550056,0.8175434932744745,0.7398313984576091,0.9134747069047049,0.9366147058724053,6251
|
||||
0,original_protean,,0.5215401253860467,0.8164397897152784,0.7424713724903063,0.9132536187826642,0.9325633790408211,6251
|
||||
1,support_weighted_beta0,0.0,0.6149565583112706,0.8840480614116488,0.7481414866548026,0.9150346064324361,0.936639326767345,34503
|
||||
1,support_weighted_beta0.25,0.25,0.6239486814341287,0.8792922611742557,0.7603617953346529,0.9308792551786822,0.9470644667115391,34503
|
||||
1,support_weighted_beta0.5,0.5,0.6241440493793726,0.8767262170299326,0.7617524315559205,0.9326111121346672,0.9483435473557725,34503
|
||||
1,support_weighted_beta0.75,0.75,0.6227556605510454,0.8735090614297254,0.760892457216182,0.9315302368713574,0.948108554127343,34503
|
||||
1,support_weighted_beta1,1.0,0.6232924200007843,0.8737177698080465,0.7609723172928275,0.9303081108634105,0.9474974643912258,34503
|
||||
1,original_protean,,0.6140607772418322,0.8832376049795277,0.7473954752926397,0.9138984591386161,0.9359372345770101,34503
|
||||
2,support_weighted_beta0,0.0,0.6769134994486486,0.8697300463882018,0.7665278503215258,0.9353501483132819,0.9493509225589307,25454
|
||||
2,support_weighted_beta0.25,0.25,0.6804540750903417,0.8683250414082848,0.7694886410056997,0.9377268456252188,0.9514515014238083,25454
|
||||
2,support_weighted_beta0.5,0.5,0.6797040888050662,0.8656806653880937,0.7691786586117774,0.9373522240850943,0.9517397334421744,25454
|
||||
2,support_weighted_beta0.75,0.75,0.6818030330757768,0.8614213642190379,0.7710071142485787,0.9383655446444473,0.9527370622407395,25454
|
||||
2,support_weighted_beta1,1.0,0.6778812872568115,0.8519182432551166,0.768904784319351,0.9378251070127924,0.9526696898622818,25454
|
||||
2,original_protean,,0.6760680764285393,0.8698349315628103,0.7656800124975965,0.9345763398861396,0.9489075724365953,25454
|
||||
|
@@ -0,0 +1,16 @@
|
||||
seed,beta,eligible_clients,val_rare_macro_f1_per_client_mean,val_rare_macro_f1_global,val_rare_recall_per_client_mean,val_rare_recall_global,val_macro_f1_global,val_accuracy_global,val_weighted_f1_global,manifest_content_hash,manifest_reload_ok
|
||||
0,0.0,10,0.4968030483665248,0.5321842753971767,0.767123922208763,0.8434122012006723,0.7478654844759977,0.9139828530719533,0.9328796664278028,759f7e504a7d442101238726334d121a746ea4a8ff366428c1c174e47f358723,True
|
||||
0,0.25,10,0.49689164333224206,0.5253607447075239,0.7613947716196803,0.8326111022258643,0.7475747316917567,0.9151251627484216,0.9353537558278756,759f7e504a7d442101238726334d121a746ea4a8ff366428c1c174e47f358723,True
|
||||
0,0.5,10,0.5043877141202036,0.519202362155984,0.7687367097840493,0.8299681909897326,0.7457804482445981,0.9143267742648684,0.9357700514425147,759f7e504a7d442101238726334d121a746ea4a8ff366428c1c174e47f358723,True
|
||||
0,0.75,10,0.4868678388015365,0.5059791333985771,0.7591333629660815,0.8213315336369041,0.73875155455023,0.9122755300071241,0.9345233223672026,759f7e504a7d442101238726334d121a746ea4a8ff366428c1c174e47f358723,True
|
||||
0,1.0,10,0.4791460442705821,0.5095808367175779,0.7622760804636377,0.8395702028345727,0.7422188468383369,0.9134792541823273,0.9368135783299136,759f7e504a7d442101238726334d121a746ea4a8ff366428c1c174e47f358723,True
|
||||
1,0.0,10,0.408275533608052,0.616817956399038,0.754665437307818,0.8854035731191047,0.7479236317732632,0.9132335961873879,0.9345027089244908,4a50ba219de20af14f6ad73976111659fba2d5b25cd5eeb1a2f21b76de0d9303,True
|
||||
1,0.25,10,0.4213860377549875,0.6285138461507458,0.7485835659627889,0.8838394567296944,0.7620867873734481,0.9298155108458005,0.9455221242928524,4a50ba219de20af14f6ad73976111659fba2d5b25cd5eeb1a2f21b76de0d9303,True
|
||||
1,0.5,10,0.42291889812447636,0.6287507126613177,0.748057250173315,0.8809534563907879,0.7635606910486206,0.9313140246149311,0.9467047228241616,4a50ba219de20af14f6ad73976111659fba2d5b25cd5eeb1a2f21b76de0d9303,True
|
||||
1,0.75,10,0.42105300844804255,0.6272153373812799,0.7445246973558585,0.8772426931488553,0.7627901276398765,0.9302945439359324,0.946551862963426,4a50ba219de20af14f6ad73976111659fba2d5b25cd5eeb1a2f21b76de0d9303,True
|
||||
1,1.0,10,0.4195341132365321,0.6248938719987901,0.7423576087482635,0.8706702441246158,0.7608708175869595,0.9283784115754047,0.9455080926483148,4a50ba219de20af14f6ad73976111659fba2d5b25cd5eeb1a2f21b76de0d9303,True
|
||||
2,0.0,10,0.5100384955477162,0.6744545474581303,0.8400788299431212,0.8822751493554857,0.7645378615044433,0.9333775517724224,0.9479975783243778,922b7bb15169302be7dd4d4eb1644d077537872e1e91fe59b7525b7e3343cc1c,True
|
||||
2,0.25,10,0.5048266072068142,0.6767452417760219,0.8428459007067381,0.8813951731999575,0.7665707279896854,0.9354533618296608,0.9497948130360396,922b7bb15169302be7dd4d4eb1644d077537872e1e91fe59b7525b7e3343cc1c,True
|
||||
2,0.5,10,0.5029418356652336,0.6754912324051592,0.8427994149308334,0.8768404426853021,0.7659466505323781,0.9352322696342152,0.9501375444947393,922b7bb15169302be7dd4d4eb1644d077537872e1e91fe59b7525b7e3343cc1c,True
|
||||
2,0.75,10,0.5097020028384487,0.6755706592622893,0.8385289625444609,0.872743230623395,0.7663509457920489,0.9356621711253593,0.9507749532058173,922b7bb15169302be7dd4d4eb1644d077537872e1e91fe59b7525b7e3343cc1c,True
|
||||
2,1.0,10,0.5071355294127556,0.6718668330746665,0.8392924763376357,0.8639074843144491,0.7644306550255252,0.9351217235364925,0.9507690806626906,922b7bb15169302be7dd4d4eb1644d077537872e1e91fe59b7525b7e3343cc1c,True
|
||||
|
@@ -0,0 +1,6 @@
|
||||
beta,n_seeds,pooled_val_rare_macro_f1_per_client_mean,std_sample_val_rare_macro_f1,std_pop_val_rare_macro_f1,min_val_rare_macro_f1,max_val_rare_macro_f1,pooled_val_rare_recall_per_client_mean,pooled_val_rare_recall_global
|
||||
0.0,3,0.471705692507431,0.055329314644425844,0.04517619623224806,0.408275533608052,0.5100384955477162,0.7872893964865675,0.8703636412250875
|
||||
0.25,3,0.47436809609801456,0.04605501919031881,0.037603765703456124,0.4213860377549875,0.5048266072068142,0.7842747460964024,0.8659485773851721
|
||||
0.5,3,0.47674948263663786,0.04662425884469754,0.038068547934984834,0.42291889812447636,0.5043877141202036,0.7865311249627326,0.8625873633552743
|
||||
0.75,3,0.47254095002934254,0.04602831582869046,0.03758196249998729,0.42105300844804255,0.5097020028384487,0.7807290076221336,0.8571058191363848
|
||||
1.0,3,0.46860522897329,0.044741855341153436,0.0365315719104147,0.4195341132365321,0.5071355294127556,0.7813087218498457,0.8580493104245459
|
||||
|
+11444
File diff suppressed because it is too large.
Load diff
+46
@@ -0,0 +1,46 @@
|
||||
class_id,class_name,beta,n_contributors,support_min,support_max,support_mean,prototype_norm,reference_norm_beta0,displacement_from_beta0,relative_displacement
|
||||
0,C&C,0.0,8,5,760,250.5,4.770216201951287,4.770216201951287,0.0,0.0
|
||||
0,C&C,0.25,8,5,760,250.5,4.770933620669477,4.770216201951287,0.5331960545497143,0.11177607722090396
|
||||
0,C&C,0.5,8,5,760,250.5,4.806200928662211,4.770216201951287,0.906150829989417,0.18996011745101832
|
||||
0,C&C,0.75,8,5,760,250.5,4.852457874791064,4.770216201951287,1.1878246302832278,0.24900855223235807
|
||||
0,C&C,1.0,8,5,760,250.5,4.904691273831403,4.770216201951287,1.4228961841681715,0.2982875668373536
|
||||
1,Exfiltration,0.0,10,27,4392,1549.4,6.913601626841314,6.913601626841314,0.0,0.0
|
||||
1,Exfiltration,0.25,10,27,4392,1549.4,7.3083719164159655,6.913601626841314,0.6980068807644447,0.10096139732068278
|
||||
1,Exfiltration,0.5,10,27,4392,1549.4,7.5607287360894055,6.913601626841314,1.1031761525926143,0.1595660571921951
|
||||
1,Exfiltration,0.75,10,27,4392,1549.4,7.72505379532629,6.913601626841314,1.3602590280897369,0.19675114383343664
|
||||
1,Exfiltration,1.0,10,27,4392,1549.4,7.841452472432679,6.913601626841314,1.545544115617925,0.22355122540146316
|
||||
2,Exploitation,0.0,9,1,240,88.11111111111111,5.0459044928503,5.0459044928503,0.0,0.0
|
||||
2,Exploitation,0.25,9,1,240,88.11111111111111,4.842915477069257,5.0459044928503,0.5897511508531448,0.11687719252094081
|
||||
2,Exploitation,0.5,9,1,240,88.11111111111111,4.732041372523653,5.0459044928503,0.93909585013325,0.18611050832687862
|
||||
2,Exploitation,0.75,9,1,240,88.11111111111111,4.660947710797605,5.0459044928503,1.1636103575185945,0.2306049112041955
|
||||
2,Exploitation,1.0,9,1,240,88.11111111111111,4.608120888995209,5.0459044928503,1.321824115607462,0.2619597967976595
|
||||
3,Lateral_movement,0.0,10,190,5435,2211.7,5.059389779434741,5.059389779434741,0.0,0.0
|
||||
3,Lateral_movement,0.25,10,190,5435,2211.7,5.23605354531631,5.059389779434741,0.48598101871177335,0.09605526355909061
|
||||
3,Lateral_movement,0.5,10,190,5435,2211.7,5.421665249177248,5.059389779434741,0.8804925334176525,0.17403136975068667
|
||||
3,Lateral_movement,0.75,10,190,5435,2211.7,5.587183727825234,5.059389779434741,1.1836615527086873,0.23395342211426368
|
||||
3,Lateral_movement,1.0,10,190,5435,2211.7,5.722036406004218,5.059389779434741,1.4102706773584788,0.2787432356152723
|
||||
4,Normal,0.0,10,1151,92460,29277.7,5.376392652358199,5.376392652358199,0.0,0.0
|
||||
4,Normal,0.25,10,1151,92460,29277.7,5.681990984928166,5.376392652358199,0.43497131021382573,0.0809039328671499
|
||||
4,Normal,0.5,10,1151,92460,29277.7,5.917124669801446,5.376392652358199,0.7645382774267853,0.14220283503501976
|
||||
4,Normal,0.75,10,1151,92460,29277.7,6.10380702212231,5.376392652358199,1.023762039001287,0.19041801914379214
|
||||
4,Normal,1.0,10,1151,92460,29277.7,6.264058179240484,5.376392652358199,1.241539979132905,0.23092435010086912
|
||||
5,RDOS,0.0,10,347,22821,9888.3,8.422547979280347,8.422547979280347,0.0,0.0
|
||||
5,RDOS,0.25,10,347,22821,9888.3,8.620918061670896,8.422547979280347,0.4150693163669237,0.049280730414122106
|
||||
5,RDOS,0.5,10,347,22821,9888.3,8.75203818871594,8.422547979280347,0.6915069239012192,0.08210186817603668
|
||||
5,RDOS,0.75,10,347,22821,9888.3,8.8343730275656,8.422547979280347,0.8730027165584727,0.10365066707914025
|
||||
5,RDOS,1.0,10,347,22821,9888.3,8.888047764356555,8.422547979280347,0.9989098237543187,0.11859948155969652
|
||||
6,Reconnaissance,0.0,10,458,23824,8916.1,5.4315535155841825,5.4315535155841825,0.0,0.0
|
||||
6,Reconnaissance,0.25,10,458,23824,8916.1,5.660090963965236,5.4315535155841825,0.5376024764747891,0.09897766356021405
|
||||
6,Reconnaissance,0.5,10,458,23824,8916.1,5.875435929367915,5.4315535155841825,0.9554020858885306,0.17589849444496797
|
||||
6,Reconnaissance,0.75,10,458,23824,8916.1,6.050569988897634,5.4315535155841825,1.2477469868993738,0.22972193559712617
|
||||
6,Reconnaissance,1.0,10,458,23824,8916.1,6.182111898039249,5.4315535155841825,1.4403595556867412,0.2651837179830908
|
||||
7,Tampering,0.0,10,31,1227,358.6,4.706517869218987,4.706517869218987,0.0,0.0
|
||||
7,Tampering,0.25,10,31,1227,358.6,4.732695239198885,4.706517869218987,0.4954736962043322,0.10527394349116802
|
||||
7,Tampering,0.5,10,31,1227,358.6,4.800394814968305,4.706517869218987,0.9972201076239648,0.21188065897844904
|
||||
7,Tampering,0.75,10,31,1227,358.6,4.894369256116969,4.706517869218987,1.4405774092634833,0.3060813640345398
|
||||
7,Tampering,1.0,10,31,1227,358.6,4.988010172720971,4.706517869218987,1.7857948642169272,0.37943016766093085
|
||||
8,Weaponization,0.0,10,285,12915,4509.4,6.188427323891787,6.188427323891787,0.0,0.0
|
||||
8,Weaponization,0.25,10,285,12915,4509.4,6.406125706681027,6.188427323891787,0.47266743210924217,0.07637924910007514
|
||||
8,Weaponization,0.5,10,285,12915,4509.4,6.600258090509457,6.188427323891787,0.8725595523209223,0.14099859409388454
|
||||
8,Weaponization,0.75,10,285,12915,4509.4,6.763071657325928,6.188427323891787,1.1938030191978883,0.1929089503223135
|
||||
8,Weaponization,1.0,10,285,12915,4509.4,6.892762983819524,6.188427323891787,1.4401830467817407,0.2327219778798398
|
||||
|
+436
@@ -0,0 +1,436 @@
|
||||
class_id,class_name,beta,client_id,N_ij,weight
|
||||
0,C&C,0.0,0,196.0,0.125
|
||||
0,C&C,0.0,1,387.0,0.125
|
||||
0,C&C,0.0,3,229.0,0.125
|
||||
0,C&C,0.0,5,760.0,0.125
|
||||
0,C&C,0.0,6,179.0,0.125
|
||||
0,C&C,0.0,7,215.0,0.125
|
||||
0,C&C,0.0,8,5.0,0.125
|
||||
0,C&C,0.0,9,33.0,0.125
|
||||
0,C&C,0.25,0,196.0,0.1303862851887575
|
||||
0,C&C,0.25,1,387.0,0.15455947558098102
|
||||
0,C&C,0.25,3,229.0,0.13555850320497126
|
||||
0,C&C,0.25,5,760.0,0.182966378613902
|
||||
0,C&C,0.25,6,179.0,0.12746212423991282
|
||||
0,C&C,0.25,7,215.0,0.13343738095108978
|
||||
0,C&C,0.25,8,5.0,0.052108718808452095
|
||||
0,C&C,0.25,9,33.0,0.08352113341193354
|
||||
0,C&C,0.5,0,196.0,0.12455986315218183
|
||||
0,C&C,0.5,1,387.0,0.17502720968912192
|
||||
0,C&C,0.5,3,229.0,0.13463805462151734
|
||||
0,C&C,0.5,5,760.0,0.2452770323204801
|
||||
0,C&C,0.5,6,179.0,0.11903552788163703
|
||||
0,C&C,0.5,7,215.0,0.13045757959232882
|
||||
0,C&C,0.5,8,5.0,0.019894594376882128
|
||||
0,C&C,0.5,9,33.0,0.05111013836585088
|
||||
0,C&C,0.75,0,196.0,0.11254353491012732
|
||||
0,C&C,0.75,1,387.0,0.1874613421805779
|
||||
0,C&C,0.75,3,229.0,0.12647512291249882
|
||||
0,C&C,0.75,5,760.0,0.3109844634890461
|
||||
0,C&C,0.75,6,179.0,0.10514007237140707
|
||||
0,C&C,0.75,7,215.0,0.12063055982856306
|
||||
0,C&C,0.75,8,5.0,0.007183829257529567
|
||||
0,C&C,0.75,9,33.0,0.029581075050250132
|
||||
0,C&C,1.0,0,196.0,0.09780439121756487
|
||||
0,C&C,1.0,1,387.0,0.19311377245508982
|
||||
0,C&C,1.0,3,229.0,0.11427145708582834
|
||||
0,C&C,1.0,5,760.0,0.37924151696606784
|
||||
0,C&C,1.0,6,179.0,0.08932135728542914
|
||||
0,C&C,1.0,7,215.0,0.10728542914171657
|
||||
0,C&C,1.0,8,5.0,0.00249500998003992
|
||||
0,C&C,1.0,9,33.0,0.016467065868263474
|
||||
1,Exfiltration,0.0,0,2293.0,0.1
|
||||
1,Exfiltration,0.0,1,189.0,0.1
|
||||
1,Exfiltration,0.0,2,1021.0,0.1
|
||||
1,Exfiltration,0.0,3,583.0,0.1
|
||||
1,Exfiltration,0.0,4,27.0,0.1
|
||||
1,Exfiltration,0.0,5,998.0,0.1
|
||||
1,Exfiltration,0.0,6,996.0,0.1
|
||||
1,Exfiltration,0.0,7,4392.0,0.1
|
||||
1,Exfiltration,0.0,8,1887.0,0.1
|
||||
1,Exfiltration,0.0,9,3108.0,0.1
|
||||
1,Exfiltration,0.25,0,2293.0,0.12159343307170532
|
||||
1,Exfiltration,0.25,1,189.0,0.06515152082780579
|
||||
1,Exfiltration,0.25,2,1021.0,0.09932659376736219
|
||||
1,Exfiltration,0.25,3,583.0,0.08634282331883751
|
||||
1,Exfiltration,0.25,4,27.0,0.04005438315169255
|
||||
1,Exfiltration,0.25,5,998.0,0.0987624243522787
|
||||
1,Exfiltration,0.25,6,996.0,0.0987129069517303
|
||||
1,Exfiltration,0.25,7,4392.0,0.1430456612614522
|
||||
1,Exfiltration,0.25,8,1887.0,0.11581160538794916
|
||||
1,Exfiltration,0.25,9,3108.0,0.13119864790918626
|
||||
1,Exfiltration,0.5,0,2293.0,0.13621594174403237
|
||||
1,Exfiltration,0.5,1,189.0,0.03910720806719513
|
||||
1,Exfiltration,0.5,2,1021.0,0.09089474612408872
|
||||
1,Exfiltration,0.5,3,583.0,0.06868472872321581
|
||||
1,Exfiltration,0.5,4,27.0,0.014781135287979606
|
||||
1,Exfiltration,0.5,5,998.0,0.08986512455006254
|
||||
1,Exfiltration,0.5,6,996.0,0.08977503417698943
|
||||
1,Exfiltration,0.5,7,4392.0,0.18851984570681085
|
||||
1,Exfiltration,0.5,8,1887.0,0.12356966235581841
|
||||
1,Exfiltration,0.5,9,3108.0,0.15858657326380718
|
||||
1,Exfiltration,0.75,0,2293.0,0.14467625167971232
|
||||
1,Exfiltration,0.75,1,189.0,0.02225566422755699
|
||||
1,Exfiltration,0.75,2,1021.0,0.07886122408377366
|
||||
1,Exfiltration,0.75,3,583.0,0.05180189215605438
|
||||
1,Exfiltration,0.75,4,27.0,0.005171505971080007
|
||||
1,Exfiltration,0.75,5,998.0,0.07752506040685822
|
||||
1,Exfiltration,0.75,6,996.0,0.07740851056204912
|
||||
1,Exfiltration,0.75,7,4392.0,0.23555425623629098
|
||||
1,Exfiltration,0.75,8,1887.0,0.1250037761406236
|
||||
1,Exfiltration,0.75,9,3108.0,0.18174185853600067
|
||||
1,Exfiltration,1.0,0,2293.0,0.14799277139537886
|
||||
1,Exfiltration,1.0,1,189.0,0.012198270298179941
|
||||
1,Exfiltration,1.0,2,1021.0,0.06589647605524719
|
||||
1,Exfiltration,1.0,3,583.0,0.03762746869756035
|
||||
1,Exfiltration,1.0,4,27.0,0.0017426100425971343
|
||||
1,Exfiltration,1.0,5,998.0,0.06441203046340518
|
||||
1,Exfiltration,1.0,6,996.0,0.06428294823802762
|
||||
1,Exfiltration,1.0,7,4392.0,0.28346456692913385
|
||||
1,Exfiltration,1.0,8,1887.0,0.12178907964373306
|
||||
1,Exfiltration,1.0,9,3108.0,0.2005937782367368
|
||||
2,Exploitation,0.0,0,96.0,0.1111111111111111
|
||||
2,Exploitation,0.0,1,136.0,0.1111111111111111
|
||||
2,Exploitation,0.0,2,30.0,0.1111111111111111
|
||||
2,Exploitation,0.0,3,1.0,0.1111111111111111
|
||||
2,Exploitation,0.0,4,175.0,0.1111111111111111
|
||||
2,Exploitation,0.0,5,30.0,0.1111111111111111
|
||||
2,Exploitation,0.0,6,240.0,0.1111111111111111
|
||||
2,Exploitation,0.0,7,11.0,0.1111111111111111
|
||||
2,Exploitation,0.0,8,74.0,0.1111111111111111
|
||||
2,Exploitation,0.25,0,96.0,0.1274858864228119
|
||||
2,Exploitation,0.25,1,136.0,0.1390845939127072
|
||||
2,Exploitation,0.25,2,30.0,0.09531793244262936
|
||||
2,Exploitation,0.25,3,1.0,0.04072811400928958
|
||||
2,Exploitation,0.25,4,175.0,0.14813368000497626
|
||||
2,Exploitation,0.25,5,30.0,0.09531793244262936
|
||||
2,Exploitation,0.25,6,240.0,0.16030501540080552
|
||||
2,Exploitation,0.25,7,11.0,0.07417242379152335
|
||||
2,Exploitation,0.25,8,74.0,0.11945442157262746
|
||||
2,Exploitation,0.5,0,96.0,0.13230838400933911
|
||||
2,Exploitation,0.5,1,136.0,0.15747847581647645
|
||||
2,Exploitation,0.5,2,30.0,0.07396263515950711
|
||||
2,Exploitation,0.5,3,1.0,0.013503667896462252
|
||||
2,Exploitation,0.5,4,175.0,0.17863673520622914
|
||||
2,Exploitation,0.5,5,30.0,0.07396263515950711
|
||||
2,Exploitation,0.5,6,240.0,0.20919792350285618
|
||||
2,Exploitation,0.5,7,11.0,0.04478659970613306
|
||||
2,Exploitation,0.5,8,74.0,0.11616294354348959
|
||||
2,Exploitation,0.75,0,96.0,0.12913781998819865
|
||||
2,Exploitation,0.75,1,136.0,0.16768885803534894
|
||||
2,Exploitation,0.75,2,30.0,0.05397479070181141
|
||||
2,Exploitation,0.75,3,1.0,0.0042106585576627015
|
||||
2,Exploitation,0.75,4,175.0,0.20259492515382302
|
||||
2,Exploitation,0.75,5,30.0,0.05397479070181141
|
||||
2,Exploitation,0.75,6,240.0,0.2567488205335074
|
||||
2,Exploitation,0.75,7,11.0,0.02543282130026652
|
||||
2,Exploitation,0.75,8,74.0,0.10623651502757
|
||||
2,Exploitation,1.0,0,96.0,0.1210592686002522
|
||||
2,Exploitation,1.0,1,136.0,0.17150063051702397
|
||||
2,Exploitation,1.0,2,30.0,0.03783102143757881
|
||||
2,Exploitation,1.0,3,1.0,0.0012610340479192938
|
||||
2,Exploitation,1.0,4,175.0,0.22068095838587642
|
||||
2,Exploitation,1.0,5,30.0,0.03783102143757881
|
||||
2,Exploitation,1.0,6,240.0,0.3026481715006305
|
||||
2,Exploitation,1.0,7,11.0,0.013871374527112233
|
||||
2,Exploitation,1.0,8,74.0,0.09331651954602774
|
||||
3,Lateral_movement,0.0,0,1364.0,0.1
|
||||
3,Lateral_movement,0.0,1,5435.0,0.1
|
||||
3,Lateral_movement,0.0,2,190.0,0.1
|
||||
3,Lateral_movement,0.0,3,1149.0,0.1
|
||||
3,Lateral_movement,0.0,4,2323.0,0.1
|
||||
3,Lateral_movement,0.0,5,211.0,0.1
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||||
3,Lateral_movement,0.0,6,552.0,0.1
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||||
3,Lateral_movement,0.0,7,5142.0,0.1
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||||
3,Lateral_movement,0.0,8,1137.0,0.1
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||||
3,Lateral_movement,0.0,9,4614.0,0.1
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||||
3,Lateral_movement,0.25,0,1364.0,0.09752285556671428
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||||
3,Lateral_movement,0.25,1,5435.0,0.13778524217741628
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||||
3,Lateral_movement,0.25,2,190.0,0.059578726655288544
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||||
3,Lateral_movement,0.25,3,1149.0,0.09342924169324289
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||||
3,Lateral_movement,0.25,4,2323.0,0.11140767713931198
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||||
3,Lateral_movement,0.25,5,211.0,0.06116083846707454
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||||
3,Lateral_movement,0.25,6,552.0,0.07778351883453181
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||||
3,Lateral_movement,0.25,7,5142.0,0.13588947940976545
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||||
3,Lateral_movement,0.25,8,1137.0,0.09318433987100772
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||||
3,Lateral_movement,0.25,9,4614.0,0.1322580801856465
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||||
3,Lateral_movement,0.5,0,1364.0,0.0883745301852826
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||||
3,Lateral_movement,0.5,1,5435.0,0.17640858119664707
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||||
3,Lateral_movement,0.5,2,190.0,0.03298349962091361
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||||
3,Lateral_movement,0.5,3,1149.0,0.08111103575645019
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||||
3,Lateral_movement,0.5,4,2323.0,0.11533059637282189
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||||
3,Lateral_movement,0.5,5,211.0,0.03475851074638393
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||||
3,Lateral_movement,0.5,6,552.0,0.056219822711156275
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||||
3,Lateral_movement,0.5,7,5142.0,0.17158762734997013
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||||
3,Lateral_movement,0.5,8,1137.0,0.08068636772991924
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||||
3,Lateral_movement,0.5,9,4614.0,0.1625394283304551
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||||
3,Lateral_movement,0.75,0,1364.0,0.07550274332458219
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||||
3,Lateral_movement,0.75,1,5435.0,0.21293723733377795
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||||
3,Lateral_movement,0.75,2,190.0,0.01721540145068439
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||||
3,Lateral_movement,0.75,3,1149.0,0.06638836535709525
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||||
3,Lateral_movement,0.75,4,2323.0,0.11256123805300046
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||||
3,Lateral_movement,0.75,5,211.0,0.018623606865947835
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||||
3,Lateral_movement,0.75,6,552.0,0.038309480451443945
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||||
3,Lateral_movement,0.75,7,5142.0,0.2042683157851929
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||||
3,Lateral_movement,0.75,8,1137.0,0.06586767021123613
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||||
3,Lateral_movement,0.75,9,4614.0,0.18832594116703902
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||||
3,Lateral_movement,1.0,0,1364.0,0.061672017000497355
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||||
3,Lateral_movement,1.0,1,5435.0,0.24573857213907854
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||||
3,Lateral_movement,1.0,2,190.0,0.00859067685490799
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||||
3,Lateral_movement,1.0,3,1149.0,0.05195098792783832
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||||
3,Lateral_movement,1.0,4,2323.0,0.10503232807342767
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||||
3,Lateral_movement,1.0,5,211.0,0.009540172717818872
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||||
3,Lateral_movement,1.0,6,552.0,0.02495817696794321
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||||
3,Lateral_movement,1.0,7,5142.0,0.23249084414703622
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||||
3,Lateral_movement,1.0,8,1137.0,0.05140841886331781
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||||
3,Lateral_movement,1.0,9,4614.0,0.208617805308134
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||||
4,Normal,0.0,0,24224.0,0.1
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||||
4,Normal,0.0,1,8909.0,0.1
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||||
4,Normal,0.0,2,92460.0,0.1
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||||
4,Normal,0.0,3,1151.0,0.1
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||||
4,Normal,0.0,4,52309.0,0.1
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||||
4,Normal,0.0,5,19915.0,0.1
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||||
4,Normal,0.0,6,1197.0,0.1
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||||
4,Normal,0.0,7,13274.0,0.1
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||||
4,Normal,0.0,8,43549.0,0.1
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||||
4,Normal,0.0,9,35789.0,0.1
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||||
4,Normal,0.25,0,24224.0,0.10638199683445329
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||||
4,Normal,0.25,1,8909.0,0.0828445442714927
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||||
4,Normal,0.25,2,92460.0,0.1486945824770311
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||||
4,Normal,0.25,3,1151.0,0.04966786641680359
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||||
4,Normal,0.25,4,52309.0,0.1289587390268249
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||||
4,Normal,0.25,5,19915.0,0.10129820533418933
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||||
4,Normal,0.25,6,1197.0,0.05015684508101685
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||||
4,Normal,0.25,7,13274.0,0.09152866475892639
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||||
4,Normal,0.25,8,43549.0,0.12318312580180278
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||||
4,Normal,0.25,9,35789.0,0.11728542999745906
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||||
4,Normal,0.5,0,24224.0,0.1033790561711709
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||||
4,Normal,0.5,1,8909.0,0.0626937306034349
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||||
4,Normal,0.5,2,92460.0,0.20196986652900872
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||||
4,Normal,0.5,3,1151.0,0.022534467281638628
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||||
4,Normal,0.5,4,52309.0,0.1519140152429214
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||||
4,Normal,0.5,5,19915.0,0.09373456953819172
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||||
4,Normal,0.5,6,1197.0,0.02298035371689658
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||||
4,Normal,0.5,7,13274.0,0.07652626909536876
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||||
4,Normal,0.5,8,43549.0,0.13861132894781109
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||||
4,Normal,0.5,9,35789.0,0.12565634287355737
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||||
4,Normal,0.75,0,24224.0,0.09448368883494875
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||||
4,Normal,0.75,1,8909.0,0.04462150010672678
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||||
4,Normal,0.75,2,92460.0,0.2580107873958497
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||||
4,Normal,0.75,3,1151.0,0.009615656486567897
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||||
4,Normal,0.75,4,52309.0,0.1683080004719624
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||||
4,Normal,0.75,5,19915.0,0.08157511230724461
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||||
4,Normal,0.75,6,1197.0,0.009902459163731267
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||||
4,Normal,0.75,7,13274.0,0.06017606806235102
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||||
4,Normal,0.75,8,43549.0,0.1466918843817802
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||||
4,Normal,0.75,9,35789.0,0.1266148427888373
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||||
4,Normal,1.0,0,24224.0,0.08273873972340723
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||||
4,Normal,1.0,1,8909.0,0.03042930284824286
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||||
4,Normal,1.0,2,92460.0,0.3158034954931569
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||||
4,Normal,1.0,3,1151.0,0.003931319741646373
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||||
4,Normal,1.0,4,52309.0,0.17866499076088627
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||||
4,Normal,1.0,5,19915.0,0.06802105356636622
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||||
4,Normal,1.0,6,1197.0,0.0040884359085583905
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||||
4,Normal,1.0,7,13274.0,0.04533826086065504
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||||
4,Normal,1.0,8,43549.0,0.1487446076706845
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||||
4,Normal,1.0,9,35789.0,0.1222397934263962
|
||||
5,RDOS,0.0,0,22821.0,0.1
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||||
5,RDOS,0.0,1,347.0,0.1
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||||
5,RDOS,0.0,2,2604.0,0.1
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||||
5,RDOS,0.0,3,438.0,0.1
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||||
5,RDOS,0.0,4,13676.0,0.1
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||||
5,RDOS,0.0,5,13907.0,0.1
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||||
5,RDOS,0.0,6,8278.0,0.1
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||||
5,RDOS,0.0,7,5873.0,0.1
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||||
5,RDOS,0.0,8,21253.0,0.1
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||||
5,RDOS,0.0,9,9686.0,0.1
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||||
5,RDOS,0.25,0,22821.0,0.1361328429302611
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||||
5,RDOS,0.25,1,347.0,0.04780371132726004
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||||
5,RDOS,0.25,2,2604.0,0.07912058531958338
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||||
5,RDOS,0.25,3,438.0,0.050669634793878406
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||||
5,RDOS,0.25,4,13676.0,0.11977578324086639
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||||
5,RDOS,0.25,5,13907.0,0.12027839109444344
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||||
5,RDOS,0.25,6,8278.0,0.10564783507845661
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||||
5,RDOS,0.25,7,5873.0,0.09696036611059587
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||||
5,RDOS,0.25,8,21253.0,0.13373168202055793
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||||
5,RDOS,0.25,9,9686.0,0.10987916808409678
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||||
5,RDOS,0.5,0,22821.0,0.17005354695400557
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||||
5,RDOS,0.5,1,347.0,0.02096925962031269
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||||
5,RDOS,0.5,2,2604.0,0.05744322963341024
|
||||
5,RDOS,0.5,3,438.0,0.023558922015854678
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||||
5,RDOS,0.5,4,13676.0,0.13164304078852693
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||||
5,RDOS,0.5,5,13907.0,0.13275017022818972
|
||||
5,RDOS,0.5,6,8278.0,0.10241912716239546
|
||||
5,RDOS,0.5,7,5873.0,0.08626772788312224
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||||
5,RDOS,0.5,8,21253.0,0.1641075192403036
|
||||
5,RDOS,0.5,9,9686.0,0.11078745647387883
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||||
5,RDOS,0.75,0,22821.0,0.20142569446520742
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||||
5,RDOS,0.75,1,347.0,0.00872189737937085
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||||
5,RDOS,0.75,2,2604.0,0.03954527512319236
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||||
5,RDOS,0.75,3,438.0,0.010386505353813502
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||||
5,RDOS,0.75,4,13676.0,0.1371933893757377
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||||
5,RDOS,0.75,5,13907.0,0.13892773568412825
|
||||
5,RDOS,0.75,6,8278.0,0.09414731373144296
|
||||
5,RDOS,0.75,7,5873.0,0.0727794663882302
|
||||
5,RDOS,0.75,8,21253.0,0.1909541265965821
|
||||
5,RDOS,0.75,9,9686.0,0.10591859590229473
|
||||
5,RDOS,1.0,0,22821.0,0.23078790085252268
|
||||
5,RDOS,1.0,1,347.0,0.0035091977387417452
|
||||
5,RDOS,1.0,2,2604.0,0.026334152483237765
|
||||
5,RDOS,1.0,3,438.0,0.004429477261005431
|
||||
5,RDOS,1.0,4,13676.0,0.13830486534591385
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||||
5,RDOS,1.0,5,13907.0,0.140640959517814
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||||
5,RDOS,1.0,6,8278.0,0.08371509764064601
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||||
5,RDOS,1.0,7,5873.0,0.059393424552248615
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||||
5,RDOS,1.0,8,21253.0,0.21493077677659456
|
||||
5,RDOS,1.0,9,9686.0,0.09795414783127535
|
||||
6,Reconnaissance,0.0,0,1040.0,0.1
|
||||
6,Reconnaissance,0.0,1,4622.0,0.1
|
||||
6,Reconnaissance,0.0,2,2096.0,0.1
|
||||
6,Reconnaissance,0.0,3,16930.0,0.1
|
||||
6,Reconnaissance,0.0,4,1111.0,0.1
|
||||
6,Reconnaissance,0.0,5,6989.0,0.1
|
||||
6,Reconnaissance,0.0,6,8453.0,0.1
|
||||
6,Reconnaissance,0.0,7,23824.0,0.1
|
||||
6,Reconnaissance,0.0,8,458.0,0.1
|
||||
6,Reconnaissance,0.0,9,23638.0,0.1
|
||||
6,Reconnaissance,0.25,0,1040.0,0.0659930999959639
|
||||
6,Reconnaissance,0.25,1,4622.0,0.0958181276250867
|
||||
6,Reconnaissance,0.25,2,2096.0,0.0786299526937229
|
||||
6,Reconnaissance,0.25,3,16930.0,0.13255753953360563
|
||||
6,Reconnaissance,0.25,4,1111.0,0.06709168658642577
|
||||
6,Reconnaissance,0.25,5,6989.0,0.10625367377162571
|
||||
6,Reconnaissance,0.25,6,8453.0,0.11142763477680856
|
||||
6,Reconnaissance,0.25,7,23824.0,0.14437562088118575
|
||||
6,Reconnaissance,0.25,8,458.0,0.05375966630332169
|
||||
6,Reconnaissance,0.25,9,23638.0,0.14409299783225335
|
||||
6,Reconnaissance,0.5,0,1040.0,0.03959357678449744
|
||||
6,Reconnaissance,0.5,1,4622.0,0.08346858237252697
|
||||
6,Reconnaissance,0.5,2,2096.0,0.056208721368085024
|
||||
6,Reconnaissance,0.5,3,16930.0,0.15974841064409478
|
||||
6,Reconnaissance,0.5,4,1111.0,0.04092277694020133
|
||||
6,Reconnaissance,0.5,5,6989.0,0.1026397503855708
|
||||
6,Reconnaissance,0.5,6,8453.0,0.11287909047811179
|
||||
6,Reconnaissance,0.5,7,23824.0,0.18950270220668675
|
||||
6,Reconnaissance,0.5,8,458.0,0.026274883915175233
|
||||
6,Reconnaissance,0.5,9,23638.0,0.18876150490504984
|
||||
6,Reconnaissance,0.75,0,1040.0,0.02206716147021742
|
||||
6,Reconnaissance,0.75,1,4622.0,0.06754511170247603
|
||||
6,Reconnaissance,0.75,2,2096.0,0.03732629869740737
|
||||
6,Reconnaissance,0.75,3,16930.0,0.17883980471096422
|
||||
6,Reconnaissance,0.75,4,1111.0,0.023187664745583814
|
||||
6,Reconnaissance,0.75,5,6989.0,0.09210490283362326
|
||||
6,Reconnaissance,0.75,6,8453.0,0.10622570451196123
|
||||
6,Reconnaissance,0.75,7,23824.0,0.23106410185546572
|
||||
6,Reconnaissance,0.75,8,458.0,0.01192945427486296
|
||||
6,Reconnaissance,0.75,9,23638.0,0.22970979519743806
|
||||
6,Reconnaissance,1.0,0,1040.0,0.011664292684021041
|
||||
6,Reconnaissance,1.0,1,4622.0,0.05183880844763966
|
||||
6,Reconnaissance,1.0,2,2096.0,0.023508036024719327
|
||||
6,Reconnaissance,1.0,3,16930.0,0.18988122609661176
|
||||
6,Reconnaissance,1.0,4,1111.0,0.012460604973026323
|
||||
6,Reconnaissance,1.0,5,6989.0,0.07838628996982985
|
||||
6,Reconnaissance,1.0,6,8453.0,0.09480602505579794
|
||||
6,Reconnaissance,1.0,7,23824.0,0.26720202779242047
|
||||
6,Reconnaissance,1.0,8,458.0,0.005136775047386189
|
||||
6,Reconnaissance,1.0,9,23638.0,0.26511591390854744
|
||||
7,Tampering,0.0,0,85.0,0.1
|
||||
7,Tampering,0.0,1,95.0,0.1
|
||||
7,Tampering,0.0,2,126.0,0.1
|
||||
7,Tampering,0.0,3,88.0,0.1
|
||||
7,Tampering,0.0,4,704.0,0.1
|
||||
7,Tampering,0.0,5,31.0,0.1
|
||||
7,Tampering,0.0,6,111.0,0.1
|
||||
7,Tampering,0.0,7,121.0,0.1
|
||||
7,Tampering,0.0,8,1227.0,0.1
|
||||
7,Tampering,0.0,9,998.0,0.1
|
||||
7,Tampering,0.25,0,85.0,0.07951995210219298
|
||||
7,Tampering,0.25,1,95.0,0.08176214560135531
|
||||
7,Tampering,0.25,2,126.0,0.08774331021966088
|
||||
7,Tampering,0.25,3,88.0,0.08021249891166626
|
||||
7,Tampering,0.25,4,704.0,0.1349008055867253
|
||||
7,Tampering,0.25,5,31.0,0.061796204517935015
|
||||
7,Tampering,0.25,6,111.0,0.08500649762510619
|
||||
7,Tampering,0.25,7,121.0,0.08685957918008103
|
||||
7,Tampering,0.25,8,1227.0,0.15500029297312884
|
||||
7,Tampering,0.25,9,998.0,0.14719871328214823
|
||||
7,Tampering,0.5,0,85.0,0.05768407068908925
|
||||
7,Tampering,0.5,1,95.0,0.06098292346030546
|
||||
7,Tampering,0.5,2,126.0,0.07023146214853088
|
||||
7,Tampering,0.5,3,88.0,0.058693198021698686
|
||||
7,Tampering,0.5,4,704.0,0.16600943332267198
|
||||
7,Tampering,0.5,5,31.0,0.03483591999294765
|
||||
7,Tampering,0.5,6,111.0,0.06591859268649537
|
||||
7,Tampering,0.5,7,121.0,0.06882387524885321
|
||||
7,Tampering,0.5,8,1227.0,0.21916374801720714
|
||||
7,Tampering,0.5,9,998.0,0.19765677641220036
|
||||
7,Tampering,0.75,0,85.0,0.038341038766087215
|
||||
7,Tampering,0.75,1,95.0,0.041676609873002285
|
||||
7,Tampering,0.75,2,126.0,0.0515083442403762
|
||||
7,Tampering,0.75,3,88.0,0.03935153564056846
|
||||
7,Tampering,0.75,4,704.0,0.18718850468018872
|
||||
7,Tampering,0.75,5,31.0,0.017993719705785484
|
||||
7,Tampering,0.75,6,111.0,0.046837306808873075
|
||||
7,Tampering,0.75,7,121.0,0.049967625095170366
|
||||
7,Tampering,0.75,8,1227.0,0.2839442658654908
|
||||
7,Tampering,0.75,9,998.0,0.24319104932445743
|
||||
7,Tampering,1.0,0,85.0,0.023703290574456217
|
||||
7,Tampering,1.0,1,95.0,0.02649191299498048
|
||||
7,Tampering,1.0,2,126.0,0.03513664249860569
|
||||
7,Tampering,1.0,3,88.0,0.024539877300613498
|
||||
7,Tampering,1.0,4,704.0,0.19631901840490798
|
||||
7,Tampering,1.0,5,31.0,0.00864472950362521
|
||||
7,Tampering,1.0,6,111.0,0.0309537088678193
|
||||
7,Tampering,1.0,7,121.0,0.03374233128834356
|
||||
7,Tampering,1.0,8,1227.0,0.34216397099832685
|
||||
7,Tampering,1.0,9,998.0,0.27830451756832125
|
||||
8,Weaponization,0.0,0,1114.0,0.1
|
||||
8,Weaponization,0.0,1,4116.0,0.1
|
||||
8,Weaponization,0.0,2,2046.0,0.1
|
||||
8,Weaponization,0.0,3,9065.0,0.1
|
||||
8,Weaponization,0.0,4,285.0,0.1
|
||||
8,Weaponization,0.0,5,4276.0,0.1
|
||||
8,Weaponization,0.0,6,8798.0,0.1
|
||||
8,Weaponization,0.0,7,1393.0,0.1
|
||||
8,Weaponization,0.0,8,12915.0,0.1
|
||||
8,Weaponization,0.0,9,1086.0,0.1
|
||||
8,Weaponization,0.25,0,1114.0,0.0773802797262321
|
||||
8,Weaponization,0.25,1,4116.0,0.10728224157220344
|
||||
8,Weaponization,0.25,2,2046.0,0.09008145762767909
|
||||
8,Weaponization,0.25,3,9065.0,0.13069258550510743
|
||||
8,Weaponization,0.25,4,285.0,0.05503262296332154
|
||||
8,Weaponization,0.25,5,4276.0,0.10830996656478618
|
||||
8,Weaponization,0.25,6,8798.0,0.12971941666995307
|
||||
8,Weaponization,0.25,7,1393.0,0.08182702782617397
|
||||
8,Weaponization,0.25,8,12915.0,0.14278500472950179
|
||||
8,Weaponization,0.25,9,1086.0,0.07688939681504137
|
||||
8,Weaponization,0.5,0,1114.0,0.05581675781681416
|
||||
8,Weaponization,0.5,1,4116.0,0.10729011085025031
|
||||
8,Weaponization,0.5,2,2046.0,0.07564405916462533
|
||||
8,Weaponization,0.5,3,9065.0,0.1592230413362216
|
||||
8,Weaponization,0.5,4,285.0,0.028232181733242087
|
||||
8,Weaponization,0.5,5,4276.0,0.10935555756019506
|
||||
8,Weaponization,0.5,6,8798.0,0.15686064258213261
|
||||
8,Weaponization,0.5,7,1393.0,0.06241623515148613
|
||||
8,Weaponization,0.5,8,12915.0,0.19005058738545788
|
||||
8,Weaponization,0.5,9,1086.0,0.05511082641957486
|
||||
8,Weaponization,0.75,0,1114.0,0.037993686295278314
|
||||
8,Weaponization,0.75,1,4116.0,0.10125210573445334
|
||||
8,Weaponization,0.75,2,2046.0,0.05994138333690149
|
||||
8,Weaponization,0.75,3,9065.0,0.18305154371433421
|
||||
8,Weaponization,0.75,4,285.0,0.013667251443010179
|
||||
8,Weaponization,0.75,5,4276.0,0.10418994572919951
|
||||
8,Weaponization,0.75,6,8798.0,0.17899277767882313
|
||||
8,Weaponization,0.75,7,1393.0,0.04492735764039096
|
||||
8,Weaponization,0.75,8,12915.0,0.23870875477782033
|
||||
8,Weaponization,0.75,9,1086.0,0.037275193649788464
|
||||
8,Weaponization,1.0,0,1114.0,0.024703951745243268
|
||||
8,Weaponization,1.0,1,4116.0,0.09127600124185035
|
||||
8,Weaponization,1.0,2,2046.0,0.045371889830132614
|
||||
8,Weaponization,1.0,3,9065.0,0.20102452654455139
|
||||
8,Weaponization,1.0,4,285.0,0.006320131281323457
|
||||
8,Weaponization,1.0,5,4276.0,0.09482414511908457
|
||||
8,Weaponization,1.0,6,8798.0,0.19510356144941676
|
||||
8,Weaponization,1.0,7,1393.0,0.030891027631170444
|
||||
8,Weaponization,1.0,8,12915.0,0.28640173859049983
|
||||
8,Weaponization,1.0,9,1086.0,0.02408302656672728
|
||||
|
+11706
File diff suppressed because it is too large.
Load diff
+46
@@ -0,0 +1,46 @@
|
||||
class_id,class_name,beta,n_contributors,support_min,support_max,support_mean,prototype_norm,reference_norm_beta0,displacement_from_beta0,relative_displacement
|
||||
0,C&C,0.0,9,87,538,222.66666666666666,5.2354116809681015,5.2354116809681015,0.0,0.0
|
||||
0,C&C,0.25,9,87,538,222.66666666666666,5.194898907510961,5.2354116809681015,0.1577100781963558,0.030123720503139682
|
||||
0,C&C,0.5,9,87,538,222.66666666666666,5.155313631927924,5.2354116809681015,0.3264883941700919,0.06236155130969941
|
||||
0,C&C,0.75,9,87,538,222.66666666666666,5.118106845104449,5.2354116809681015,0.503350519095841,0.09614344578204487
|
||||
0,C&C,1.0,9,87,538,222.66666666666666,5.084592774124751,5.2354116809681015,0.6847690195463256,0.13079563963147636
|
||||
1,Exfiltration,0.0,10,239,3749,1549.4,7.629732378880332,7.629732378880332,0.0,0.0
|
||||
1,Exfiltration,0.25,10,239,3749,1549.4,7.817142412720884,7.629732378880332,0.4303188395756118,0.05640025340426964
|
||||
1,Exfiltration,0.5,10,239,3749,1549.4,7.994655852497228,7.629732378880332,0.8191503402527969,0.10736291911368556
|
||||
1,Exfiltration,0.75,10,239,3749,1549.4,8.149645160263951,7.629732378880332,1.1487441777538223,0.15056152964599803
|
||||
1,Exfiltration,1.0,10,239,3749,1549.4,8.275373211658478,7.629732378880332,1.412557214087583,0.18513850079429348
|
||||
2,Exploitation,0.0,10,4,246,79.3,5.8218656423809385,5.8218656423809385,0.0,0.0
|
||||
2,Exploitation,0.25,10,4,246,79.3,5.652871510884149,5.8218656423809385,0.4510869619381431,0.07748151359839084
|
||||
2,Exploitation,0.5,10,4,246,79.3,5.507328970331381,5.8218656423809385,0.8626986133797654,0.14818250134452637
|
||||
2,Exploitation,0.75,10,4,246,79.3,5.4010378837670645,5.8218656423809385,1.2071859088476515,0.20735379052031075
|
||||
2,Exploitation,1.0,10,4,246,79.3,5.333587731233961,5.8218656423809385,1.4809450323140279,0.2543763671791597
|
||||
3,Lateral_movement,0.0,10,556,4082,2211.7,6.151659891092278,6.151659891092278,0.0,0.0
|
||||
3,Lateral_movement,0.25,10,556,4082,2211.7,6.212923499176303,6.151659891092278,0.2574665523313587,0.041853183838101195
|
||||
3,Lateral_movement,0.5,10,556,4082,2211.7,6.278615321442222,6.151659891092278,0.47846985675017045,0.07777898408249195
|
||||
3,Lateral_movement,0.75,10,556,4082,2211.7,6.342700038280084,6.151659891092278,0.6579842973620211,0.10696044791338272
|
||||
3,Lateral_movement,1.0,10,556,4082,2211.7,6.40117093616851,6.151659891092278,0.7972700943677291,0.1296024338930362
|
||||
4,Normal,0.0,10,4311,73956,29277.7,6.080540042706397,6.080540042706397,0.0,0.0
|
||||
4,Normal,0.25,10,4311,73956,29277.7,6.161691208699456,6.080540042706397,0.24171855410307602,0.03975281017892765
|
||||
4,Normal,0.5,10,4311,73956,29277.7,6.237042705205876,6.080540042706397,0.4580105900010111,0.07532399865541457
|
||||
4,Normal,0.75,10,4311,73956,29277.7,6.30263304536083,6.080540042706397,0.6410962139477815,0.10543409128877886
|
||||
4,Normal,1.0,10,4311,73956,29277.7,6.357166086112595,6.080540042706397,0.790165471090536,0.12994988365191987
|
||||
5,RDOS,0.0,10,268,34051,9888.3,8.745269146187699,8.745269146187699,0.0,0.0
|
||||
5,RDOS,0.25,10,268,34051,9888.3,9.03411572146646,8.745269146187699,0.4163257737915561,0.047605827428769745
|
||||
5,RDOS,0.5,10,268,34051,9888.3,9.185056176057977,8.745269146187699,0.6406803639277195,0.07326022255209945
|
||||
5,RDOS,0.75,10,268,34051,9888.3,9.247185104440781,8.745269146187699,0.7596839292072829,0.08686798730928136
|
||||
5,RDOS,1.0,10,268,34051,9888.3,9.262011657019244,8.745269146187699,0.8417540230265395,0.09625250051834974
|
||||
6,Reconnaissance,0.0,10,520,22127,8916.1,6.446948181605699,6.446948181605699,0.0,0.0
|
||||
6,Reconnaissance,0.25,10,520,22127,8916.1,6.624071043084189,6.446948181605699,0.3201710656233807,0.0496624226850289
|
||||
6,Reconnaissance,0.5,10,520,22127,8916.1,6.760744507264429,6.446948181605699,0.5594016353982239,0.08676999095390547
|
||||
6,Reconnaissance,0.75,10,520,22127,8916.1,6.860664364055998,6.446948181605699,0.7348048246100566,0.11397715692931838
|
||||
6,Reconnaissance,1.0,10,520,22127,8916.1,6.932487056600201,6.446948181605699,0.8651809801835829,0.13420008286278765
|
||||
7,Tampering,0.0,10,25,1004,358.6,5.43666794523019,5.43666794523019,0.0,0.0
|
||||
7,Tampering,0.25,10,25,1004,358.6,5.3045456539896705,5.43666794523019,0.5004494949194306,0.09205077447455574
|
||||
7,Tampering,0.5,10,25,1004,358.6,5.254785805438766,5.43666794523019,0.9327814268885475,0.17157226379935794
|
||||
7,Tampering,0.75,10,25,1004,358.6,5.260345407405032,5.43666794523019,1.2965161502244944,0.2384762437739058
|
||||
7,Tampering,1.0,10,25,1004,358.6,5.297100096405528,5.43666794523019,1.6015145240420323,0.29457648327540514
|
||||
8,Weaponization,0.0,10,269,10726,4509.4,6.8722286037153655,6.8722286037153655,0.0,0.0
|
||||
8,Weaponization,0.25,10,269,10726,4509.4,7.094902285598923,6.8722286037153655,0.4759060944845105,0.06925062042133161
|
||||
8,Weaponization,0.5,10,269,10726,4509.4,7.277217698433601,6.8722286037153655,0.8478196060028891,0.12336894694459499
|
||||
8,Weaponization,0.75,10,269,10726,4509.4,7.413264641461658,6.8722286037153655,1.121875452958101,0.16324769120043187
|
||||
8,Weaponization,1.0,10,269,10726,4509.4,7.509687300167426,6.8722286037153655,1.3197795639990293,0.19204535240365994
|
||||
|
+446
@@ -0,0 +1,446 @@
|
||||
class_id,class_name,beta,client_id,N_ij,weight
|
||||
0,C&C,0.0,0,212.0,0.1111111111111111
|
||||
0,C&C,0.0,1,332.0,0.1111111111111111
|
||||
0,C&C,0.0,2,538.0,0.1111111111111111
|
||||
0,C&C,0.0,3,110.0,0.1111111111111111
|
||||
0,C&C,0.0,4,116.0,0.1111111111111111
|
||||
0,C&C,0.0,5,284.0,0.1111111111111111
|
||||
0,C&C,0.0,6,87.0,0.1111111111111111
|
||||
0,C&C,0.0,7,131.0,0.1111111111111111
|
||||
0,C&C,0.0,9,194.0,0.1111111111111111
|
||||
0,C&C,0.25,0,212.0,0.11324399767749505
|
||||
0,C&C,0.25,1,332.0,0.12668224405587436
|
||||
0,C&C,0.25,2,538.0,0.14293111968509725
|
||||
0,C&C,0.25,3,110.0,0.09611239473189447
|
||||
0,C&C,0.25,4,116.0,0.0973970323430312
|
||||
0,C&C,0.25,5,284.0,0.12183184242761845
|
||||
0,C&C,0.25,6,87.0,0.09063815156054919
|
||||
0,C&C,0.25,7,131.0,0.10040354590879214
|
||||
0,C&C,0.25,9,194.0,0.11075967160964781
|
||||
0,C&C,0.5,0,212.0,0.11305578617568617
|
||||
0,C&C,0.5,1,332.0,0.1414796268677369
|
||||
0,C&C,0.5,2,538.0,0.18010094920597988
|
||||
0,C&C,0.5,3,110.0,0.08143689496533879
|
||||
0,C&C,0.5,4,116.0,0.08362841361126731
|
||||
0,C&C,0.5,5,284.0,0.13085310545150017
|
||||
0,C&C,0.5,6,87.0,0.07242433066554983
|
||||
0,C&C,0.5,7,131.0,0.08887109100821904
|
||||
0,C&C,0.5,9,194.0,0.1081498020487219
|
||||
0,C&C,0.75,0,212.0,0.11051433471609325
|
||||
0,C&C,0.75,1,332.0,0.1547106749136364
|
||||
0,C&C,0.75,2,538.0,0.2222047941041352
|
||||
0,C&C,0.75,3,110.0,0.06756335882094086
|
||||
0,C&C,0.75,4,116.0,0.07030888486386021
|
||||
0,C&C,0.75,5,284.0,0.13761173579890018
|
||||
0,C&C,0.75,6,87.0,0.05666386021106064
|
||||
0,C&C,0.75,7,131.0,0.07702295735456736
|
||||
0,C&C,0.75,9,194.0,0.10339939921680594
|
||||
0,C&C,1.0,0,212.0,0.10578842315369262
|
||||
0,C&C,1.0,1,332.0,0.1656686626746507
|
||||
0,C&C,1.0,2,538.0,0.2684630738522954
|
||||
0,C&C,1.0,3,110.0,0.054890219560878244
|
||||
0,C&C,1.0,4,116.0,0.05788423153692615
|
||||
0,C&C,1.0,5,284.0,0.14171656686626746
|
||||
0,C&C,1.0,6,87.0,0.04341317365269461
|
||||
0,C&C,1.0,7,131.0,0.06536926147704591
|
||||
0,C&C,1.0,9,194.0,0.0968063872255489
|
||||
1,Exfiltration,0.0,0,3749.0,0.1
|
||||
1,Exfiltration,0.0,1,705.0,0.1
|
||||
1,Exfiltration,0.0,2,3265.0,0.1
|
||||
1,Exfiltration,0.0,3,292.0,0.1
|
||||
1,Exfiltration,0.0,4,239.0,0.1
|
||||
1,Exfiltration,0.0,5,977.0,0.1
|
||||
1,Exfiltration,0.0,6,1227.0,0.1
|
||||
1,Exfiltration,0.0,7,3716.0,0.1
|
||||
1,Exfiltration,0.0,8,485.0,0.1
|
||||
1,Exfiltration,0.0,9,839.0,0.1
|
||||
1,Exfiltration,0.25,0,3749.0,0.1349255613503203
|
||||
1,Exfiltration,0.25,1,705.0,0.0888510680612849
|
||||
1,Exfiltration,0.25,2,3265.0,0.13034253700120838
|
||||
1,Exfiltration,0.25,3,292.0,0.07127891599472466
|
||||
1,Exfiltration,0.25,4,239.0,0.06779768248716028
|
||||
1,Exfiltration,0.25,5,977.0,0.0964026593432908
|
||||
1,Exfiltration,0.25,6,1227.0,0.10205317346715201
|
||||
1,Exfiltration,0.25,7,3716.0,0.13462766079260258
|
||||
1,Exfiltration,0.25,8,485.0,0.0809190560906004
|
||||
1,Exfiltration,0.25,9,839.0,0.09280168541165575
|
||||
1,Exfiltration,0.5,0,3749.0,0.1721361260945726
|
||||
1,Exfiltration,0.5,1,705.0,0.07464639924202042
|
||||
1,Exfiltration,0.5,2,3265.0,0.16064081453740153
|
||||
1,Exfiltration,0.5,3,292.0,0.04804030217899038
|
||||
1,Exfiltration,0.5,4,239.0,0.04346235504600115
|
||||
1,Exfiltration,0.5,5,977.0,0.08787424094801437
|
||||
1,Exfiltration,0.5,6,1227.0,0.09847740279077387
|
||||
1,Exfiltration,0.5,7,3716.0,0.17137685056798274
|
||||
1,Exfiltration,0.5,8,485.0,0.061913474124455886
|
||||
1,Exfiltration,0.5,9,839.0,0.08143203446978702
|
||||
1,Exfiltration,0.75,0,3749.0,0.20862371791834747
|
||||
1,Exfiltration,0.75,1,705.0,0.05957567041001592
|
||||
1,Exfiltration,0.75,2,3265.0,0.1880786460308486
|
||||
1,Exfiltration,0.75,3,292.0,0.03075843531201997
|
||||
1,Exfiltration,0.75,4,239.0,0.026468268170412996
|
||||
1,Exfiltration,0.75,5,977.0,0.07609358109777584
|
||||
1,Exfiltration,0.75,6,1227.0,0.09027355023057035
|
||||
1,Exfiltration,0.75,7,3716.0,0.20724491310240978
|
||||
1,Exfiltration,0.75,8,485.0,0.045002164662563765
|
||||
1,Exfiltration,0.75,9,839.0,0.06788105306503524
|
||||
1,Exfiltration,1.0,0,3749.0,0.24196463147024655
|
||||
1,Exfiltration,1.0,1,705.0,0.04550148444559184
|
||||
1,Exfiltration,1.0,2,3265.0,0.2107267329288757
|
||||
1,Exfiltration,1.0,3,292.0,0.018846004905124565
|
||||
1,Exfiltration,1.0,4,239.0,0.015425325932619078
|
||||
1,Exfiltration,1.0,5,977.0,0.06305666709694076
|
||||
1,Exfiltration,1.0,6,1227.0,0.07919194526913644
|
||||
1,Exfiltration,1.0,7,3716.0,0.2398347747515167
|
||||
1,Exfiltration,1.0,8,485.0,0.031302439654059634
|
||||
1,Exfiltration,1.0,9,839.0,0.05414999354588873
|
||||
2,Exploitation,0.0,0,8.0,0.1
|
||||
2,Exploitation,0.0,1,39.0,0.1
|
||||
2,Exploitation,0.0,2,114.0,0.1
|
||||
2,Exploitation,0.0,3,22.0,0.1
|
||||
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|
||||
6,Reconnaissance,1.0,8,12507.0,0.14027433519139534
|
||||
6,Reconnaissance,1.0,9,22127.0,0.24816904251858996
|
||||
7,Tampering,0.0,0,102.0,0.1
|
||||
7,Tampering,0.0,1,82.0,0.1
|
||||
7,Tampering,0.0,2,312.0,0.1
|
||||
7,Tampering,0.0,3,69.0,0.1
|
||||
7,Tampering,0.0,4,754.0,0.1
|
||||
7,Tampering,0.0,5,1004.0,0.1
|
||||
7,Tampering,0.0,6,25.0,0.1
|
||||
7,Tampering,0.0,7,504.0,0.1
|
||||
7,Tampering,0.0,8,297.0,0.1
|
||||
7,Tampering,0.0,9,437.0,0.1
|
||||
7,Tampering,0.25,0,102.0,0.07977041433631873
|
||||
7,Tampering,0.25,1,82.0,0.07553448421448694
|
||||
7,Tampering,0.25,2,312.0,0.10549465431981336
|
||||
7,Tampering,0.25,3,69.0,0.07234425981936646
|
||||
7,Tampering,0.25,4,754.0,0.13153297448552895
|
||||
7,Tampering,0.25,5,1004.0,0.14129449224720045
|
||||
7,Tampering,0.25,6,25.0,0.05612764326239511
|
||||
7,Tampering,0.25,7,504.0,0.11893219630110058
|
||||
7,Tampering,0.25,8,297.0,0.10420316669726913
|
||||
7,Tampering,0.25,9,437.0,0.11476571431652025
|
||||
7,Tampering,0.5,0,102.0,0.05945843659044485
|
||||
7,Tampering,0.5,1,82.0,0.05331142925559283
|
||||
7,Tampering,0.5,2,312.0,0.10398978893666252
|
||||
7,Tampering,0.5,3,69.0,0.04890327508608459
|
||||
7,Tampering,0.5,4,754.0,0.16165869651049217
|
||||
7,Tampering,0.5,5,1004.0,0.18654355808709883
|
||||
7,Tampering,0.5,6,25.0,0.02943631244963168
|
||||
7,Tampering,0.5,7,504.0,0.13216871509986014
|
||||
7,Tampering,0.5,8,297.0,0.1014592445699859
|
||||
7,Tampering,0.5,9,437.0,0.12307054341414651
|
||||
7,Tampering,0.75,0,102.0,0.041985889067966596
|
||||
7,Tampering,0.75,1,82.0,0.03564623077802597
|
||||
7,Tampering,0.75,2,312.0,0.09711116644830438
|
||||
7,Tampering,0.75,3,69.0,0.03131771324182069
|
||||
7,Tampering,0.75,4,754.0,0.18822691944657582
|
||||
7,Tampering,0.75,5,1004.0,0.23332082842726642
|
||||
7,Tampering,0.75,6,25.0,0.014625416128545142
|
||||
7,Tampering,0.75,7,504.0,0.13914773053453158
|
||||
7,Tampering,0.75,8,297.0,0.09358808528318041
|
||||
7,Tampering,0.75,9,437.0,0.12503002064378305
|
||||
7,Tampering,1.0,0,102.0,0.02844394868934746
|
||||
7,Tampering,1.0,1,82.0,0.02286670384829894
|
||||
7,Tampering,1.0,2,312.0,0.08700501952035694
|
||||
7,Tampering,1.0,3,69.0,0.0192414947016174
|
||||
7,Tampering,1.0,4,754.0,0.2102621305075293
|
||||
7,Tampering,1.0,5,1004.0,0.2799776910206358
|
||||
7,Tampering,1.0,6,25.0,0.006971556051310652
|
||||
7,Tampering,1.0,7,504.0,0.14054656999442275
|
||||
7,Tampering,1.0,8,297.0,0.08282208588957055
|
||||
7,Tampering,1.0,9,437.0,0.12186279977691021
|
||||
8,Weaponization,0.0,0,1779.0,0.1
|
||||
8,Weaponization,0.0,1,791.0,0.1
|
||||
8,Weaponization,0.0,2,5753.0,0.1
|
||||
8,Weaponization,0.0,3,755.0,0.1
|
||||
8,Weaponization,0.0,4,9193.0,0.1
|
||||
8,Weaponization,0.0,5,10726.0,0.1
|
||||
8,Weaponization,0.0,6,7997.0,0.1
|
||||
8,Weaponization,0.0,7,269.0,0.1
|
||||
8,Weaponization,0.0,8,3372.0,0.1
|
||||
8,Weaponization,0.0,9,4459.0,0.1
|
||||
8,Weaponization,0.25,0,1779.0,0.08657493382750385
|
||||
8,Weaponization,0.25,1,791.0,0.07069558655408409
|
||||
8,Weaponization,0.25,2,5753.0,0.11609720777592324
|
||||
8,Weaponization,0.25,3,755.0,0.06987710745280062
|
||||
8,Weaponization,0.25,4,9193.0,0.13053064868346584
|
||||
8,Weaponization,0.25,5,10726.0,0.13566181696112142
|
||||
8,Weaponization,0.25,6,7997.0,0.12606076991789908
|
||||
8,Weaponization,0.25,7,269.0,0.053986634082435835
|
||||
8,Weaponization,0.25,8,3372.0,0.10158277504522659
|
||||
8,Weaponization,0.25,9,4459.0,0.10893251969953938
|
||||
8,Weaponization,0.5,0,1779.0,0.06986069910097994
|
||||
8,Weaponization,0.5,1,791.0,0.0465836157774934
|
||||
8,Weaponization,0.5,2,5753.0,0.12562964724178405
|
||||
8,Weaponization,0.5,3,755.0,0.04551121491762885
|
||||
8,Weaponization,0.5,4,9193.0,0.1588084413631268
|
||||
8,Weaponization,0.5,5,10726.0,0.17153938535201976
|
||||
8,Weaponization,0.5,6,7997.0,0.14811822579777986
|
||||
8,Weaponization,0.5,7,269.0,0.027165712070926024
|
||||
8,Weaponization,0.5,8,3372.0,0.09618087777906575
|
||||
8,Weaponization,0.5,9,4459.0,0.11060218059919556
|
||||
8,Weaponization,0.75,0,1779.0,0.05349319493757938
|
||||
8,Weaponization,0.75,1,791.0,0.029127213484318258
|
||||
8,Weaponization,0.75,2,5753.0,0.12899930094053294
|
||||
8,Weaponization,0.75,3,755.0,0.02812721870130455
|
||||
8,Weaponization,0.75,4,9193.0,0.18334096858742452
|
||||
8,Weaponization,0.75,5,10726.0,0.20582348186232863
|
||||
8,Weaponization,0.75,6,7997.0,0.1651436572959233
|
||||
8,Weaponization,0.75,7,269.0,0.012971218835285089
|
||||
8,Weaponization,0.75,8,3372.0,0.0864136303437107
|
||||
8,Weaponization,0.75,9,4459.0,0.1065601150115926
|
||||
8,Weaponization,1.0,0,1779.0,0.039450924734998005
|
||||
8,Weaponization,1.0,1,791.0,0.017541136293076683
|
||||
8,Weaponization,1.0,2,5753.0,0.127577948285803
|
||||
8,Weaponization,1.0,3,755.0,0.016742803920698983
|
||||
8,Weaponization,1.0,4,9193.0,0.20386304164633876
|
||||
8,Weaponization,1.0,5,10726.0,0.23785869517008915
|
||||
8,Weaponization,1.0,6,7997.0,0.17734066616401295
|
||||
8,Weaponization,1.0,7,269.0,0.005965316893600035
|
||||
8,Weaponization,1.0,8,3372.0,0.07477713221271122
|
||||
8,Weaponization,1.0,9,4459.0,0.09888233467867122
|
||||
|
+11837
File diff suppressed because it is too large.
Load diff
+46
@@ -0,0 +1,46 @@
|
||||
class_id,class_name,beta,n_contributors,support_min,support_max,support_mean,prototype_norm,reference_norm_beta0,displacement_from_beta0,relative_displacement
|
||||
0,C&C,0.0,10,1,546,200.4,4.895765551089247,4.895765551089247,0.0,0.0
|
||||
0,C&C,0.25,10,1,546,200.4,4.740433762150664,4.895765551089247,0.6268193555516579,0.1280329601184024
|
||||
0,C&C,0.5,10,1,546,200.4,4.664450704736187,4.895765551089247,1.0708837976422039,0.21873674024360615
|
||||
0,C&C,0.75,10,1,546,200.4,4.6309541855833745,4.895765551089247,1.4320794500312022,0.29251389493367025
|
||||
0,C&C,1.0,10,1,546,200.4,4.625942556800833,4.895765551089247,1.7441743055076424,0.35626181182625977
|
||||
1,Exfiltration,0.0,10,9,3572,1549.4,6.540657844958708,6.540657844958708,0.0,0.0
|
||||
1,Exfiltration,0.25,10,9,3572,1549.4,6.89297509228936,6.540657844958708,0.7005731273791159,0.10711049927785035
|
||||
1,Exfiltration,0.5,10,9,3572,1549.4,7.104671009903064,6.540657844958708,1.047943424728358,0.16021988148119892
|
||||
1,Exfiltration,0.75,10,9,3572,1549.4,7.235405321360742,6.540657844958708,1.2519602938431387,0.19141198385848945
|
||||
1,Exfiltration,1.0,10,9,3572,1549.4,7.320464470003187,6.540657844958708,1.3846272466974707,0.21169541038822098
|
||||
2,Exploitation,0.0,10,11,382,79.3,5.410045122666565,5.410045122666565,0.0,0.0
|
||||
2,Exploitation,0.25,10,11,382,79.3,5.290169230004606,5.410045122666565,0.33213289764322984,0.06139189047641887
|
||||
2,Exploitation,0.5,10,11,382,79.3,5.17397790454302,5.410045122666565,0.7494922500463251,0.13853715321267168
|
||||
2,Exploitation,0.75,10,11,382,79.3,5.089744816704113,5.410045122666565,1.2548655232819537,0.23195102717802124
|
||||
2,Exploitation,1.0,10,11,382,79.3,5.067558174875309,5.410045122666565,1.8150114731665588,0.3354891561924635
|
||||
3,Lateral_movement,0.0,10,3,5709,2211.7,5.0399729106223985,5.0399729106223985,0.0,0.0
|
||||
3,Lateral_movement,0.25,10,3,5709,2211.7,5.443372116083882,5.0399729106223985,0.8950011168465136,0.1775805411493745
|
||||
3,Lateral_movement,0.5,10,3,5709,2211.7,5.646452177541357,5.0399729106223985,1.3755795607902412,0.27293391952385865
|
||||
3,Lateral_movement,0.75,10,3,5709,2211.7,5.775699768941646,5.0399729106223985,1.6836259334315673,0.3340545600717628
|
||||
3,Lateral_movement,1.0,10,3,5709,2211.7,5.873758446629449,5.0399729106223985,1.9004241105530428,0.377070302609693
|
||||
4,Normal,0.0,10,1930,64353,29277.7,5.422384598932964,5.422384598932964,0.0,0.0
|
||||
4,Normal,0.25,10,1930,64353,29277.7,5.538963278117921,5.422384598932964,0.26971503509223715,0.049741037392536235
|
||||
4,Normal,0.5,10,1930,64353,29277.7,5.6067015754668255,5.422384598932964,0.45369233971395007,0.08367026193664485
|
||||
4,Normal,0.75,10,1930,64353,29277.7,5.642503177772837,5.422384598932964,0.5824041031282855,0.10740737631242407
|
||||
4,Normal,1.0,10,1930,64353,29277.7,5.66094321238838,5.422384598932964,0.6776684342907874,0.12497609159338152
|
||||
5,RDOS,0.0,10,636,18655,9888.3,8.30513384062201,8.30513384062201,0.0,0.0
|
||||
5,RDOS,0.25,10,636,18655,9888.3,8.469674091485185,8.30513384062201,0.2637502192596181,0.03175749172994238
|
||||
5,RDOS,0.5,10,636,18655,9888.3,8.57351412083427,8.30513384062201,0.4316771118028957,0.051977140897053305
|
||||
5,RDOS,0.75,10,636,18655,9888.3,8.635033421016171,8.30513384062201,0.5354842605581158,0.06447629512470456
|
||||
5,RDOS,1.0,10,636,18655,9888.3,8.671271171669174,8.30513384062201,0.6016395266536176,0.07244188211764664
|
||||
6,Reconnaissance,0.0,10,1528,21418,8916.1,5.69844985931776,5.69844985931776,0.0,0.0
|
||||
6,Reconnaissance,0.25,10,1528,21418,8916.1,5.856534655787208,5.69844985931776,0.2038596395428698,0.035774578100311066
|
||||
6,Reconnaissance,0.5,10,1528,21418,8916.1,5.995089528571691,5.69844985931776,0.3788239457941236,0.06647842047336674
|
||||
6,Reconnaissance,0.75,10,1528,21418,8916.1,6.110849484656916,5.69844985931776,0.5243911576151126,0.09202347490303173
|
||||
6,Reconnaissance,1.0,10,1528,21418,8916.1,6.203808017221648,5.69844985931776,0.6421335927154392,0.11268566163927217
|
||||
7,Tampering,0.0,10,1,1321,358.6,4.6690951386835104,4.6690951386835104,0.0,0.0
|
||||
7,Tampering,0.25,10,1,1321,358.6,4.610947601463497,4.6690951386835104,0.9732218819818169,0.20843907718192797
|
||||
7,Tampering,0.5,10,1,1321,358.6,4.73117751009491,4.6690951386835104,1.6596964268654473,0.3554642554003327
|
||||
7,Tampering,0.75,10,1,1321,358.6,4.899015639120044,4.6690951386835104,2.110712157391946,0.4520602161015461
|
||||
7,Tampering,1.0,10,1,1321,358.6,5.061586926744909,4.6690951386835104,2.4151317063636144,0.5172590479800291
|
||||
8,Weaponization,0.0,10,169,17328,4509.4,5.882391297846072,5.882391297846072,0.0,0.0
|
||||
8,Weaponization,0.25,10,169,17328,4509.4,6.206450349845326,5.882391297846072,0.7061244249971462,0.1200403695102202
|
||||
8,Weaponization,0.5,10,169,17328,4509.4,6.4525272570581205,5.882391297846072,1.1928558529811986,0.20278417272546642
|
||||
8,Weaponization,0.75,10,169,17328,4509.4,6.609290165346632,5.882391297846072,1.4867044185381322,0.2527381031388564
|
||||
8,Weaponization,1.0,10,169,17328,4509.4,6.705192012655144,5.882391297846072,1.6559144922727265,0.28150362810428214
|
||||
|
+451
@@ -0,0 +1,451 @@
|
||||
class_id,class_name,beta,client_id,N_ij,weight
|
||||
0,C&C,0.0,0,226.0,0.1
|
||||
0,C&C,0.0,1,39.0,0.1
|
||||
0,C&C,0.0,2,1.0,0.1
|
||||
0,C&C,0.0,3,198.0,0.1
|
||||
0,C&C,0.0,4,27.0,0.1
|
||||
0,C&C,0.0,5,195.0,0.1
|
||||
0,C&C,0.0,6,167.0,0.1
|
||||
0,C&C,0.0,7,546.0,0.1
|
||||
0,C&C,0.0,8,526.0,0.1
|
||||
0,C&C,0.0,9,79.0,0.1
|
||||
0,C&C,0.25,0,226.0,0.11628502965214987
|
||||
0,C&C,0.25,1,39.0,0.07494848352076798
|
||||
0,C&C,0.25,2,1.0,0.029991397171836718
|
||||
0,C&C,0.25,3,198.0,0.11250271304094853
|
||||
0,C&C,0.25,4,27.0,0.06836560150113535
|
||||
0,C&C,0.25,5,195.0,0.11207412348715913
|
||||
0,C&C,0.25,6,167.0,0.10781416307218546
|
||||
0,C&C,0.25,7,546.0,0.14497558131805274
|
||||
0,C&C,0.25,8,526.0,0.14362932987285995
|
||||
0,C&C,0.25,9,79.0,0.08941357736290435
|
||||
0,C&C,0.5,0,226.0,0.12160666196810047
|
||||
0,C&C,0.5,1,39.0,0.05051675570470549
|
||||
0,C&C,0.5,2,1.0,0.008089154827217095
|
||||
0,C&C,0.5,3,198.0,0.11382449785569249
|
||||
0,C&C,0.5,4,27.0,0.04203248145309315
|
||||
0,C&C,0.5,5,195.0,0.11295889975847177
|
||||
0,C&C,0.5,6,167.0,0.10453491814566636
|
||||
0,C&C,0.5,7,546.0,0.18901639213836596
|
||||
0,C&C,0.5,8,526.0,0.18552225737261482
|
||||
0,C&C,0.5,9,79.0,0.07189798077607243
|
||||
0,C&C,0.75,0,226.0,0.11957893293426541
|
||||
0,C&C,0.75,1,39.0,0.032016348568671985
|
||||
0,C&C,0.75,2,1.0,0.002051508611419314
|
||||
0,C&C,0.75,3,198.0,0.1082859814210595
|
||||
0,C&C,0.75,4,27.0,0.02429943453753491
|
||||
0,C&C,0.75,5,195.0,0.10705311353022569
|
||||
0,C&C,0.75,6,167.0,0.09530390539440783
|
||||
0,C&C,0.75,7,546.0,0.231722297768339
|
||||
0,C&C,0.75,8,526.0,0.22532669797065485
|
||||
0,C&C,0.75,9,79.0,0.05436177926342155
|
||||
0,C&C,1.0,0,226.0,0.11277445109780439
|
||||
0,C&C,1.0,1,39.0,0.019461077844311378
|
||||
0,C&C,1.0,2,1.0,0.000499001996007984
|
||||
0,C&C,1.0,3,198.0,0.09880239520958084
|
||||
0,C&C,1.0,4,27.0,0.01347305389221557
|
||||
0,C&C,1.0,5,195.0,0.09730538922155689
|
||||
0,C&C,1.0,6,167.0,0.08333333333333333
|
||||
0,C&C,1.0,7,546.0,0.27245508982035926
|
||||
0,C&C,1.0,8,526.0,0.2624750499001996
|
||||
0,C&C,1.0,9,79.0,0.03942115768463074
|
||||
1,Exfiltration,0.0,0,320.0,0.1
|
||||
1,Exfiltration,0.0,1,443.0,0.1
|
||||
1,Exfiltration,0.0,2,271.0,0.1
|
||||
1,Exfiltration,0.0,3,2231.0,0.1
|
||||
1,Exfiltration,0.0,4,3050.0,0.1
|
||||
1,Exfiltration,0.0,5,3338.0,0.1
|
||||
1,Exfiltration,0.0,6,551.0,0.1
|
||||
1,Exfiltration,0.0,7,9.0,0.1
|
||||
1,Exfiltration,0.0,8,3572.0,0.1
|
||||
1,Exfiltration,0.0,9,1709.0,0.1
|
||||
1,Exfiltration,0.25,0,320.0,0.07618330760947613
|
||||
1,Exfiltration,0.25,1,443.0,0.08263675621258328
|
||||
1,Exfiltration,0.25,2,271.0,0.07308271155318115
|
||||
1,Exfiltration,0.25,3,2231.0,0.12379332338129746
|
||||
1,Exfiltration,0.25,4,3050.0,0.13385891161978417
|
||||
1,Exfiltration,0.25,5,3338.0,0.13691275601421593
|
||||
1,Exfiltration,0.25,6,551.0,0.0872690461979466
|
||||
1,Exfiltration,0.25,7,9.0,0.031198445624221978
|
||||
1,Exfiltration,0.25,8,3572.0,0.13925159946191848
|
||||
1,Exfiltration,0.25,9,1709.0,0.11581314232537485
|
||||
1,Exfiltration,0.5,0,320.0,0.052120741108611215
|
||||
1,Exfiltration,0.5,1,443.0,0.061324985797845816
|
||||
1,Exfiltration,0.5,2,271.0,0.04796453501532562
|
||||
1,Exfiltration,0.5,3,2231.0,0.13762121202131414
|
||||
1,Exfiltration,0.5,4,3050.0,0.16091091813308311
|
||||
1,Exfiltration,0.5,5,3338.0,0.1683366806812216
|
||||
1,Exfiltration,0.5,6,551.0,0.06839295882057898
|
||||
1,Exfiltration,0.5,7,9.0,0.008740914011739181
|
||||
1,Exfiltration,0.5,8,3572.0,0.17413710427289078
|
||||
1,Exfiltration,0.5,9,1709.0,0.12044995013738959
|
||||
1,Exfiltration,0.75,0,320.0,0.03347803293733215
|
||||
1,Exfiltration,0.75,1,443.0,0.042726787746117025
|
||||
1,Exfiltration,0.75,2,271.0,0.029554554463746302
|
||||
1,Exfiltration,0.75,3,2231.0,0.14363891841658866
|
||||
1,Exfiltration,0.75,4,3050.0,0.18160271125713146
|
||||
1,Exfiltration,0.75,5,3338.0,0.19431762681485712
|
||||
1,Exfiltration,0.75,6,551.0,0.050322377080212845
|
||||
1,Exfiltration,0.75,7,9.0,0.0022992136580799773
|
||||
1,Exfiltration,0.75,8,3572.0,0.2044471384092909
|
||||
1,Exfiltration,0.75,9,1709.0,0.11761263921664367
|
||||
1,Exfiltration,1.0,0,320.0,0.02065315606041048
|
||||
1,Exfiltration,1.0,1,443.0,0.02859171292113076
|
||||
1,Exfiltration,1.0,2,271.0,0.017490641538660128
|
||||
1,Exfiltration,1.0,3,2231.0,0.14399122240867432
|
||||
1,Exfiltration,1.0,4,3050.0,0.1968503937007874
|
||||
1,Exfiltration,1.0,5,3338.0,0.21543823415515684
|
||||
1,Exfiltration,1.0,6,551.0,0.0355621530915193
|
||||
1,Exfiltration,1.0,7,9.0,0.0005808700141990448
|
||||
1,Exfiltration,1.0,8,3572.0,0.230540854524332
|
||||
1,Exfiltration,1.0,9,1709.0,0.11030076158512973
|
||||
2,Exploitation,0.0,0,48.0,0.1
|
||||
2,Exploitation,0.0,1,43.0,0.1
|
||||
2,Exploitation,0.0,2,382.0,0.1
|
||||
2,Exploitation,0.0,3,25.0,0.1
|
||||
2,Exploitation,0.0,4,17.0,0.1
|
||||
2,Exploitation,0.0,5,27.0,0.1
|
||||
2,Exploitation,0.0,6,11.0,0.1
|
||||
2,Exploitation,0.0,7,67.0,0.1
|
||||
2,Exploitation,0.0,8,59.0,0.1
|
||||
2,Exploitation,0.0,9,114.0,0.1
|
||||
2,Exploitation,0.25,0,48.0,0.09791779502370136
|
||||
2,Exploitation,0.25,1,43.0,0.09526172243010055
|
||||
2,Exploitation,0.25,2,382.0,0.16446260181924036
|
||||
2,Exploitation,0.25,3,25.0,0.08318333305157002
|
||||
2,Exploitation,0.25,4,17.0,0.07553766330995358
|
||||
2,Exploitation,0.25,5,27.0,0.08479929797308287
|
||||
2,Exploitation,0.25,6,11.0,0.0677484692794147
|
||||
2,Exploitation,0.25,7,67.0,0.10643145921191847
|
||||
2,Exploitation,0.25,8,59.0,0.10310134212295713
|
||||
2,Exploitation,0.25,9,114.0,0.12155631577806096
|
||||
2,Exploitation,0.5,0,48.0,0.08973203290656045
|
||||
2,Exploitation,0.5,1,43.0,0.0849299984264485
|
||||
2,Exploitation,0.5,2,382.0,0.25313871414230854
|
||||
2,Exploitation,0.5,3,25.0,0.0647585166919188
|
||||
2,Exploitation,0.5,4,17.0,0.053401240895821114
|
||||
2,Exploitation,0.5,5,27.0,0.06729902467992034
|
||||
2,Exploitation,0.5,6,11.0,0.04295594036941237
|
||||
2,Exploitation,0.5,7,67.0,0.10601426082130917
|
||||
2,Exploitation,0.5,8,59.0,0.09948392102528207
|
||||
2,Exploitation,0.5,9,114.0,0.13828635004101858
|
||||
2,Exploitation,0.75,0,48.0,0.07647211721813353
|
||||
2,Exploitation,0.75,1,43.0,0.07041635293327168
|
||||
2,Exploitation,0.75,2,382.0,0.3623428604358123
|
||||
2,Exploitation,0.75,3,25.0,0.04688427371867725
|
||||
2,Exploitation,0.75,4,17.0,0.03510822534900022
|
||||
2,Exploitation,0.75,5,27.0,0.049670097144063764
|
||||
2,Exploitation,0.75,6,11.0,0.025328921623251364
|
||||
2,Exploitation,0.75,7,67.0,0.09820379889986246
|
||||
2,Exploitation,0.75,8,59.0,0.0892711634761329
|
||||
2,Exploitation,0.75,9,114.0,0.1463021892017945
|
||||
2,Exploitation,1.0,0,48.0,0.0605296343001261
|
||||
2,Exploitation,1.0,1,43.0,0.05422446406052964
|
||||
2,Exploitation,1.0,2,382.0,0.4817150063051702
|
||||
2,Exploitation,1.0,3,25.0,0.031525851197982346
|
||||
2,Exploitation,1.0,4,17.0,0.021437578814627996
|
||||
2,Exploitation,1.0,5,27.0,0.034047919293820936
|
||||
2,Exploitation,1.0,6,11.0,0.013871374527112233
|
||||
2,Exploitation,1.0,7,67.0,0.08448928121059268
|
||||
2,Exploitation,1.0,8,59.0,0.07440100882723834
|
||||
2,Exploitation,1.0,9,114.0,0.1437578814627995
|
||||
3,Lateral_movement,0.0,0,1483.0,0.1
|
||||
3,Lateral_movement,0.0,1,626.0,0.1
|
||||
3,Lateral_movement,0.0,2,3698.0,0.1
|
||||
3,Lateral_movement,0.0,3,2434.0,0.1
|
||||
3,Lateral_movement,0.0,4,2509.0,0.1
|
||||
3,Lateral_movement,0.0,5,5036.0,0.1
|
||||
3,Lateral_movement,0.0,6,5709.0,0.1
|
||||
3,Lateral_movement,0.0,7,3.0,0.1
|
||||
3,Lateral_movement,0.0,8,145.0,0.1
|
||||
3,Lateral_movement,0.0,9,474.0,0.1
|
||||
3,Lateral_movement,0.25,0,1483.0,0.10398897585895747
|
||||
3,Lateral_movement,0.25,1,626.0,0.08381960243516166
|
||||
3,Lateral_movement,0.25,2,3698.0,0.13067537046675748
|
||||
3,Lateral_movement,0.25,3,2434.0,0.11770154314572136
|
||||
3,Lateral_movement,0.25,4,2509.0,0.11859794902762807
|
||||
3,Lateral_movement,0.25,5,5036.0,0.1411638334799892
|
||||
3,Lateral_movement,0.25,6,5709.0,0.145660576353503
|
||||
3,Lateral_movement,0.25,7,3.0,0.02205374389858963
|
||||
3,Lateral_movement,0.25,8,145.0,0.05814923610432163
|
||||
3,Lateral_movement,0.25,9,474.0,0.07818916922937057
|
||||
3,Lateral_movement,0.5,0,1483.0,0.09489029898693696
|
||||
3,Lateral_movement,0.5,1,626.0,0.061650755940334374
|
||||
3,Lateral_movement,0.5,2,3698.0,0.14984239051079917
|
||||
3,Lateral_movement,0.5,3,2434.0,0.12156583192207791
|
||||
3,Lateral_movement,0.5,4,2509.0,0.12342455503261136
|
||||
3,Lateral_movement,0.5,5,5036.0,0.17486146002072073
|
||||
3,Lateral_movement,0.5,6,5709.0,0.1861792433818101
|
||||
3,Lateral_movement,0.5,7,3.0,0.0042678767277943485
|
||||
3,Lateral_movement,0.5,8,145.0,0.029671208860493292
|
||||
3,Lateral_movement,0.5,9,474.0,0.0536463786164218
|
||||
3,Lateral_movement,0.75,0,1483.0,0.08129510978994439
|
||||
3,Lateral_movement,0.75,1,626.0,0.042573495414691485
|
||||
3,Lateral_movement,0.75,2,3698.0,0.16131833791427233
|
||||
3,Lateral_movement,0.75,3,2434.0,0.11788240539507477
|
||||
3,Lateral_movement,0.75,4,2509.0,0.12059631975874911
|
||||
3,Lateral_movement,0.75,5,5036.0,0.20336342601201657
|
||||
3,Lateral_movement,0.75,6,5709.0,0.22342336624680512
|
||||
3,Lateral_movement,0.75,7,3.0,0.0007754423210930549
|
||||
3,Lateral_movement,0.75,8,145.0,0.014214597290042248
|
||||
3,Lateral_movement,0.75,9,474.0,0.03455749985731095
|
||||
3,Lateral_movement,1.0,0,1483.0,0.06705249355699236
|
||||
3,Lateral_movement,1.0,1,626.0,0.028304019532486322
|
||||
3,Lateral_movement,1.0,2,3698.0,0.1672017000497355
|
||||
3,Lateral_movement,1.0,3,2434.0,0.11005109192024234
|
||||
3,Lateral_movement,1.0,4,2509.0,0.11344214857349551
|
||||
3,Lateral_movement,1.0,5,5036.0,0.22769815074377175
|
||||
3,Lateral_movement,1.0,6,5709.0,0.2581272324456301
|
||||
3,Lateral_movement,1.0,7,3.0,0.00013564226613012616
|
||||
3,Lateral_movement,1.0,8,145.0,0.006556042862956097
|
||||
3,Lateral_movement,1.0,9,474.0,0.02143147804855993
|
||||
4,Normal,0.0,0,14394.0,0.1
|
||||
4,Normal,0.0,1,10435.0,0.1
|
||||
4,Normal,0.0,2,35232.0,0.1
|
||||
4,Normal,0.0,3,61429.0,0.1
|
||||
4,Normal,0.0,4,60920.0,0.1
|
||||
4,Normal,0.0,5,15350.0,0.1
|
||||
4,Normal,0.0,6,7460.0,0.1
|
||||
4,Normal,0.0,7,1930.0,0.1
|
||||
4,Normal,0.0,8,21274.0,0.1
|
||||
4,Normal,0.0,9,64353.0,0.1
|
||||
4,Normal,0.25,0,14394.0,0.09032063207154925
|
||||
4,Normal,0.25,1,10435.0,0.08334215135139734
|
||||
4,Normal,0.25,2,35232.0,0.1129733267982088
|
||||
4,Normal,0.25,3,61429.0,0.12981801223256306
|
||||
4,Normal,0.25,4,60920.0,0.12954825493167998
|
||||
4,Normal,0.25,5,15350.0,0.0917843609589061
|
||||
4,Normal,0.25,6,7460.0,0.07663484801635571
|
||||
4,Normal,0.25,7,1930.0,0.05465512863965035
|
||||
4,Normal,0.25,8,21274.0,0.09958728264368244
|
||||
4,Normal,0.25,9,64353.0,0.13133600235600693
|
||||
4,Normal,0.5,0,14394.0,0.07699438636403831
|
||||
4,Normal,0.5,1,10435.0,0.06555631593827232
|
||||
4,Normal,0.5,2,35232.0,0.12045836427809789
|
||||
4,Normal,0.5,3,61429.0,0.15905782358691617
|
||||
4,Normal,0.5,4,60920.0,0.15839747717113217
|
||||
4,Normal,0.5,5,15350.0,0.07951013718613945
|
||||
4,Normal,0.5,6,7460.0,0.05542908718440307
|
||||
4,Normal,0.5,7,1930.0,0.028193368472743556
|
||||
4,Normal,0.5,8,21274.0,0.09360367290997303
|
||||
4,Normal,0.5,9,64353.0,0.16279936690828398
|
||||
4,Normal,0.75,0,14394.0,0.06265891738090724
|
||||
4,Normal,0.75,1,10435.0,0.04922844334802152
|
||||
4,Normal,0.75,2,35232.0,0.12261673172475474
|
||||
4,Normal,0.75,3,61429.0,0.186048788884939
|
||||
4,Normal,0.75,4,60920.0,0.1848913885779064
|
||||
4,Normal,0.75,5,15350.0,0.0657548888489542
|
||||
4,Normal,0.75,6,7460.0,0.038273738362119725
|
||||
4,Normal,0.75,7,1930.0,0.013884004471676058
|
||||
4,Normal,0.75,8,21274.0,0.08399116966300586
|
||||
4,Normal,0.75,9,64353.0,0.19265192873771533
|
||||
4,Normal,1.0,0,14394.0,0.049163697968078096
|
||||
4,Normal,1.0,1,10435.0,0.03564146090710677
|
||||
4,Normal,1.0,2,35232.0,0.12033732157922242
|
||||
4,Normal,1.0,3,61429.0,0.20981497863561688
|
||||
4,Normal,1.0,4,60920.0,0.20807645409304693
|
||||
4,Normal,1.0,5,15350.0,0.052428981784771345
|
||||
4,Normal,1.0,6,7460.0,0.025480143590514284
|
||||
4,Normal,1.0,7,1930.0,0.006592047872612944
|
||||
4,Normal,1.0,8,21274.0,0.07266281162796258
|
||||
4,Normal,1.0,9,64353.0,0.21980210194106778
|
||||
5,RDOS,0.0,0,8158.0,0.1
|
||||
5,RDOS,0.0,1,14173.0,0.1
|
||||
5,RDOS,0.0,2,856.0,0.1
|
||||
5,RDOS,0.0,3,12067.0,0.1
|
||||
5,RDOS,0.0,4,6987.0,0.1
|
||||
5,RDOS,0.0,5,10151.0,0.1
|
||||
5,RDOS,0.0,6,636.0,0.1
|
||||
5,RDOS,0.0,7,15192.0,0.1
|
||||
5,RDOS,0.0,8,12008.0,0.1
|
||||
5,RDOS,0.0,9,18655.0,0.1
|
||||
5,RDOS,0.25,0,8158.0,0.10135858142918623
|
||||
5,RDOS,0.25,1,14173.0,0.11636705549761071
|
||||
5,RDOS,0.25,2,856.0,0.05768767550565062
|
||||
5,RDOS,0.25,3,12067.0,0.11178008271737916
|
||||
5,RDOS,0.25,4,6987.0,0.0975073344412102
|
||||
5,RDOS,0.25,5,10151.0,0.1070512654439126
|
||||
5,RDOS,0.25,6,636.0,0.05355855821562114
|
||||
5,RDOS,0.25,7,15192.0,0.11840453495456318
|
||||
5,RDOS,0.25,8,12008.0,0.11164319799980361
|
||||
5,RDOS,0.25,9,18655.0,0.12464171379506263
|
||||
5,RDOS,0.5,0,8158.0,0.0973861266651492
|
||||
5,RDOS,0.5,1,14173.0,0.12836189976820325
|
||||
5,RDOS,0.5,2,856.0,0.031545842076938675
|
||||
5,RDOS,0.5,3,12067.0,0.11844177272432403
|
||||
5,RDOS,0.5,4,6987.0,0.09012610742071525
|
||||
5,RDOS,0.5,5,10151.0,0.10863247052505876
|
||||
5,RDOS,0.5,6,636.0,0.0271915397286676
|
||||
5,RDOS,0.5,7,15192.0,0.13289624754024137
|
||||
5,RDOS,0.5,8,12008.0,0.11815186523525896
|
||||
5,RDOS,0.5,9,18655.0,0.14726612831544292
|
||||
5,RDOS,0.75,0,8158.0,0.09054006843005559
|
||||
5,RDOS,0.75,1,14173.0,0.13700909038112283
|
||||
5,RDOS,0.75,2,856.0,0.016691999620683576
|
||||
5,RDOS,0.75,3,12067.0,0.1214374187056476
|
||||
5,RDOS,0.75,4,6987.0,0.08060669227822206
|
||||
5,RDOS,0.75,5,10151.0,0.10666812556850644
|
||||
5,RDOS,0.75,6,636.0,0.013358136574228676
|
||||
5,RDOS,0.75,7,15192.0,0.14433254064721152
|
||||
5,RDOS,0.75,8,12008.0,0.12099183184241119
|
||||
5,RDOS,0.75,9,18655.0,0.16836409595191063
|
||||
5,RDOS,1.0,0,8158.0,0.08250154222667193
|
||||
5,RDOS,1.0,1,14173.0,0.14333100735212323
|
||||
5,RDOS,1.0,2,856.0,0.008656695286348513
|
||||
5,RDOS,1.0,3,12067.0,0.12203310983687793
|
||||
5,RDOS,1.0,4,6987.0,0.07065926397864142
|
||||
5,RDOS,1.0,5,10151.0,0.10265667506042495
|
||||
5,RDOS,1.0,6,636.0,0.00643184369406268
|
||||
5,RDOS,1.0,7,15192.0,0.15363611540911987
|
||||
5,RDOS,1.0,8,12008.0,0.12143644509167399
|
||||
5,RDOS,1.0,9,18655.0,0.1886573020640555
|
||||
6,Reconnaissance,0.0,0,5775.0,0.1
|
||||
6,Reconnaissance,0.0,1,10388.0,0.1
|
||||
6,Reconnaissance,0.0,2,1528.0,0.1
|
||||
6,Reconnaissance,0.0,3,3527.0,0.1
|
||||
6,Reconnaissance,0.0,4,21418.0,0.1
|
||||
6,Reconnaissance,0.0,5,4883.0,0.1
|
||||
6,Reconnaissance,0.0,6,8572.0,0.1
|
||||
6,Reconnaissance,0.0,7,3147.0,0.1
|
||||
6,Reconnaissance,0.0,8,16761.0,0.1
|
||||
6,Reconnaissance,0.0,9,13162.0,0.1
|
||||
6,Reconnaissance,0.25,0,5775.0,0.09431411539668508
|
||||
6,Reconnaissance,0.25,1,10388.0,0.1092249070518849
|
||||
6,Reconnaissance,0.25,2,1528.0,0.06764248237026069
|
||||
6,Reconnaissance,0.25,3,3527.0,0.08337580949066314
|
||||
6,Reconnaissance,0.25,4,21418.0,0.1308830560900735
|
||||
6,Reconnaissance,0.25,5,4883.0,0.09043996375787115
|
||||
6,Reconnaissance,0.25,6,8572.0,0.10410203977521769
|
||||
6,Reconnaissance,0.25,7,3147.0,0.08103318036484615
|
||||
6,Reconnaissance,0.25,8,16761.0,0.12310159501758605
|
||||
6,Reconnaissance,0.25,9,13162.0,0.11588285068491158
|
||||
6,Reconnaissance,0.5,0,5775.0,0.08582038912135571
|
||||
6,Reconnaissance,0.5,1,10388.0,0.1151013601077437
|
||||
6,Reconnaissance,0.5,2,1528.0,0.04414445527722864
|
||||
6,Reconnaissance,0.5,3,3527.0,0.06706828712258502
|
||||
6,Reconnaissance,0.5,4,21418.0,0.16527377321382633
|
||||
6,Reconnaissance,0.5,5,4883.0,0.07891468861741868
|
||||
6,Reconnaissance,0.5,6,8572.0,0.10455759044213475
|
||||
6,Reconnaissance,0.5,7,3147.0,0.06335236856015176
|
||||
6,Reconnaissance,0.5,8,16761.0,0.14620574836996753
|
||||
6,Reconnaissance,0.5,9,13162.0,0.12956133916758789
|
||||
6,Reconnaissance,0.75,0,5775.0,0.07561523448806375
|
||||
6,Reconnaissance,0.75,1,10388.0,0.11744763272704153
|
||||
6,Reconnaissance,0.75,2,1528.0,0.02789573620706306
|
||||
6,Reconnaissance,0.75,3,3527.0,0.052239547522218495
|
||||
6,Reconnaissance,0.75,4,21418.0,0.20208286831407052
|
||||
6,Reconnaissance,0.75,5,4883.0,0.06667459019752289
|
||||
6,Reconnaissance,0.75,6,8572.0,0.1016850095205772
|
||||
6,Reconnaissance,0.75,7,3147.0,0.047958751539421904
|
||||
6,Reconnaissance,0.75,8,16761.0,0.16813969543524018
|
||||
6,Reconnaissance,0.75,9,13162.0,0.14026093404878054
|
||||
6,Reconnaissance,1.0,0,5775.0,0.06477047139444377
|
||||
6,Reconnaissance,1.0,1,10388.0,0.11650833884770247
|
||||
6,Reconnaissance,1.0,2,1528.0,0.017137537712677068
|
||||
6,Reconnaissance,1.0,3,3527.0,0.03955765413129059
|
||||
6,Reconnaissance,1.0,4,21418.0,0.24021713529457947
|
||||
6,Reconnaissance,1.0,5,4883.0,0.05476609728468725
|
||||
6,Reconnaissance,1.0,6,8572.0,0.09614068931483497
|
||||
6,Reconnaissance,1.0,7,3147.0,0.035295701035205976
|
||||
6,Reconnaissance,1.0,8,16761.0,0.18798577853545834
|
||||
6,Reconnaissance,1.0,9,13162.0,0.14762059644912012
|
||||
7,Tampering,0.0,0,28.0,0.1
|
||||
7,Tampering,0.0,1,1321.0,0.1
|
||||
7,Tampering,0.0,2,547.0,0.1
|
||||
7,Tampering,0.0,3,123.0,0.1
|
||||
7,Tampering,0.0,4,416.0,0.1
|
||||
7,Tampering,0.0,5,1.0,0.1
|
||||
7,Tampering,0.0,6,684.0,0.1
|
||||
7,Tampering,0.0,7,416.0,0.1
|
||||
7,Tampering,0.0,8,28.0,0.1
|
||||
7,Tampering,0.0,9,22.0,0.1
|
||||
7,Tampering,0.25,0,28.0,0.06370697623820916
|
||||
7,Tampering,0.25,1,1321.0,0.16696413389441478
|
||||
7,Tampering,0.25,2,547.0,0.13393507220294634
|
||||
7,Tampering,0.25,3,123.0,0.09223032997339063
|
||||
7,Tampering,0.25,4,416.0,0.12507508802933592
|
||||
7,Tampering,0.25,5,1.0,0.027694752259253136
|
||||
7,Tampering,0.25,6,684.0,0.14163203981249994
|
||||
7,Tampering,0.25,7,416.0,0.12507508802933592
|
||||
7,Tampering,0.25,8,28.0,0.06370697623820916
|
||||
7,Tampering,0.25,9,22.0,0.059979543322405016
|
||||
7,Tampering,0.5,0,28.0,0.034350792408428615
|
||||
7,Tampering,0.5,1,1321.0,0.23594411691072328
|
||||
7,Tampering,0.5,2,547.0,0.15182783784844756
|
||||
7,Tampering,0.5,3,123.0,0.07199632022037547
|
||||
7,Tampering,0.5,4,416.0,0.13240500727747825
|
||||
7,Tampering,0.5,5,1.0,0.006491689575050542
|
||||
7,Tampering,0.5,6,684.0,0.16977971298289088
|
||||
7,Tampering,0.5,7,416.0,0.13240500727747825
|
||||
7,Tampering,0.5,8,28.0,0.034350792408428615
|
||||
7,Tampering,0.5,9,22.0,0.030448723090698526
|
||||
7,Tampering,0.75,0,28.0,0.016844128199414863
|
||||
7,Tampering,0.75,1,1321.0,0.30321950040350965
|
||||
7,Tampering,0.75,2,547.0,0.15652024152582444
|
||||
7,Tampering,0.75,3,123.0,0.05111034920374946
|
||||
7,Tampering,0.75,4,416.0,0.1274676598028691
|
||||
7,Tampering,0.75,5,1.0,0.0013838213114324117
|
||||
7,Tampering,0.75,6,684.0,0.18508536976718815
|
||||
7,Tampering,0.75,7,416.0,0.1274676598028691
|
||||
7,Tampering,0.75,8,28.0,0.016844128199414863
|
||||
7,Tampering,0.75,9,22.0,0.014057141783727934
|
||||
7,Tampering,1.0,0,28.0,0.007808142777467931
|
||||
7,Tampering,1.0,1,1321.0,0.36837702175125486
|
||||
7,Tampering,1.0,2,547.0,0.15253764640267709
|
||||
7,Tampering,1.0,3,123.0,0.034300055772448414
|
||||
7,Tampering,1.0,4,416.0,0.11600669269380925
|
||||
7,Tampering,1.0,5,1.0,0.0002788622420524261
|
||||
7,Tampering,1.0,6,684.0,0.19074177356385946
|
||||
7,Tampering,1.0,7,416.0,0.11600669269380925
|
||||
7,Tampering,1.0,8,28.0,0.007808142777467931
|
||||
7,Tampering,1.0,9,22.0,0.006134969325153374
|
||||
8,Weaponization,0.0,0,175.0,0.1
|
||||
8,Weaponization,0.0,1,3511.0,0.1
|
||||
8,Weaponization,0.0,2,169.0,0.1
|
||||
8,Weaponization,0.0,3,3814.0,0.1
|
||||
8,Weaponization,0.0,4,3668.0,0.1
|
||||
8,Weaponization,0.0,5,592.0,0.1
|
||||
8,Weaponization,0.0,6,434.0,0.1
|
||||
8,Weaponization,0.0,7,6839.0,0.1
|
||||
8,Weaponization,0.0,8,8564.0,0.1
|
||||
8,Weaponization,0.0,9,17328.0,0.1
|
||||
8,Weaponization,0.25,0,175.0,0.051763015511812394
|
||||
8,Weaponization,0.25,1,3511.0,0.10955135760866752
|
||||
8,Weaponization,0.25,2,169.0,0.051313511175866286
|
||||
8,Weaponization,0.25,3,3814.0,0.11184207829406444
|
||||
8,Weaponization,0.25,4,3668.0,0.11075603204510591
|
||||
8,Weaponization,0.25,5,592.0,0.07020054490895981
|
||||
8,Weaponization,0.25,6,434.0,0.06495797666965754
|
||||
8,Weaponization,0.25,7,6839.0,0.12942202998957816
|
||||
8,Weaponization,0.25,8,8564.0,0.1369081245235908
|
||||
8,Weaponization,0.25,9,17328.0,0.16328532927269707
|
||||
8,Weaponization,0.5,0,175.0,0.02362937207401995
|
||||
8,Weaponization,0.5,1,3511.0,0.10583969294886883
|
||||
8,Weaponization,0.5,2,169.0,0.02322076422508934
|
||||
8,Weaponization,0.5,3,3814.0,0.11031218854225817
|
||||
8,Weaponization,0.5,4,3668.0,0.10818020996410319
|
||||
8,Weaponization,0.5,5,592.0,0.04346042909331164
|
||||
8,Weaponization,0.5,6,434.0,0.03721157235375758
|
||||
8,Weaponization,0.5,7,6839.0,0.1477166528792725
|
||||
8,Weaponization,0.5,8,8564.0,0.16529947941463657
|
||||
8,Weaponization,0.5,9,17328.0,0.23512963850468224
|
||||
8,Weaponization,0.75,0,175.0,0.00986881142956876
|
||||
8,Weaponization,0.75,1,3511.0,0.09355336997693972
|
||||
8,Weaponization,0.75,2,169.0,0.009613938566119275
|
||||
8,Weaponization,0.75,3,3814.0,0.09954554546865467
|
||||
8,Weaponization,0.75,4,3668.0,0.09667369303574606
|
||||
8,Weaponization,0.75,5,592.0,0.024616573100593304
|
||||
8,Weaponization,0.75,6,434.0,0.019503098371432673
|
||||
8,Weaponization,0.75,7,6839.0,0.15425198694612802
|
||||
8,Weaponization,0.75,8,8564.0,0.18259707154614557
|
||||
8,Weaponization,0.75,9,17328.0,0.3097759115586719
|
||||
8,Weaponization,1.0,0,175.0,0.00388078236572493
|
||||
8,Weaponization,1.0,1,3511.0,0.07785958220605846
|
||||
8,Weaponization,1.0,2,169.0,0.0037477269703286467
|
||||
8,Weaponization,1.0,3,3814.0,0.08457887967357076
|
||||
8,Weaponization,1.0,4,3668.0,0.08134119838559453
|
||||
8,Weaponization,1.0,5,592.0,0.013128132345766621
|
||||
8,Weaponization,1.0,6,434.0,0.009624340266997827
|
||||
8,Weaponization,1.0,7,6839.0,0.15166097485253027
|
||||
8,Weaponization,1.0,8,8564.0,0.18991440102896173
|
||||
8,Weaponization,1.0,9,17328.0,0.3842639819044662
|
||||
|
@@ -0,0 +1,16 @@
|
||||
dataset,alpha,beta,n_seeds,pooled_val_mean,pooled_val_std_sample,pooled_val_std_pop,pooled_val_min,pooled_val_max,pooled_val_recall,selected,cells_sj_lt_M_total,cells_total,missing_client_class_cells_total,client_size_ratio_mean,support_cv_mean,union_unseen_mean,mean_displacement_beta1
|
||||
xiiotid,0.25,0.0,3,0.5917038146634539,0.08952883653922933,0.07309998892871802,0.4924247362191584,0.666306546980769,0.7594821244948339,True,19,27,38,14.745270966890343,1.4423832412721973,5.666666666666667,3.4221253316893105
|
||||
xiiotid,0.25,0.25,3,0.5886906256417319,0.06643525635398827,0.05424415966608841,0.5142371025483052,0.641922010303426,0.7807713039840465,False,19,27,38,14.745270966890343,1.4423832412721973,5.666666666666667,3.4221253316893105
|
||||
xiiotid,0.25,0.5,3,0.5858514801619258,0.044857849968223555,0.03662628112682344,0.5370398599938551,0.625267153876176,0.7725355473131942,False,19,27,38,14.745270966890343,1.4423832412721973,5.666666666666667,3.4221253316893105
|
||||
xiiotid,0.25,0.75,3,0.5794633987349401,0.0649060573642385,0.05299557391939959,0.5356723665662311,0.6540329635413089,0.7607912573123681,False,19,27,38,14.745270966890343,1.4423832412721973,5.666666666666667,3.4221253316893105
|
||||
xiiotid,0.25,1.0,3,0.5320987006423418,0.045718338534042856,0.037328867098742294,0.48696981273909073,0.5783845291609608,0.704574711153059,False,19,27,38,14.745270966890343,1.4423832412721973,5.666666666666667,3.4221253316893105
|
||||
xiiotid,0.5,0.0,3,0.5443606875936857,0.09144660841267144,0.07466584310638286,0.4471180202967977,0.6286244107933443,0.8390875794416744,False,7,27,9,7.405360903230798,1.1833344484214374,2.3333333333333335,2.0985368999756338
|
||||
xiiotid,0.5,0.25,3,0.5554339572275921,0.09006816161098347,0.07354034600581387,0.4583095088424948,0.6362049516605607,0.8412777237951431,False,7,27,9,7.405360903230798,1.1833344484214374,2.3333333333333335,2.0985368999756338
|
||||
xiiotid,0.5,0.5,3,0.5673218494926892,0.08853898624879539,0.07229177955094838,0.4710149921480162,0.6451888105578426,0.8388718664026588,False,7,27,9,7.405360903230798,1.1833344484214374,2.3333333333333335,2.0985368999756338
|
||||
xiiotid,0.5,0.75,3,0.5793667895728949,0.07512057331236716,0.06133569126687837,0.5049373198599186,0.6551599000232645,0.8290881018460031,True,7,27,9,7.405360903230798,1.1833344484214374,2.3333333333333335,2.0985368999756338
|
||||
xiiotid,0.5,1.0,3,0.5734790834215032,0.1004496749103663,0.08201681611961567,0.4858767968549885,0.6831172735008992,0.8207630276313397,False,7,27,9,7.405360903230798,1.1833344484214374,2.3333333333333335,2.0985368999756338
|
||||
xiiotid,0.75,0.0,3,0.471705692507431,0.055329314644425844,0.04517619623224806,0.408275533608052,0.5100384955477162,0.7872893964865675,False,3,27,4,4.668973713188908,0.8806570470947873,1.0,1.3051104878964057
|
||||
xiiotid,0.75,0.25,3,0.47436809609801456,0.04605501919031881,0.037603765703456124,0.4213860377549875,0.5048266072068142,0.7842747460964024,False,3,27,4,4.668973713188908,0.8806570470947873,1.0,1.3051104878964057
|
||||
xiiotid,0.75,0.5,3,0.47674948263663786,0.04662425884469754,0.038068547934984834,0.42291889812447636,0.5043877141202036,0.7865311249627326,True,3,27,4,4.668973713188908,0.8806570470947873,1.0,1.3051104878964057
|
||||
xiiotid,0.75,0.75,3,0.47254095002934254,0.04602831582869046,0.03758196249998729,0.42105300844804255,0.5097020028384487,0.7807290076221336,False,3,27,4,4.668973713188908,0.8806570470947873,1.0,1.3051104878964057
|
||||
xiiotid,0.75,1.0,3,0.46860522897329,0.044741855341153436,0.0365315719104147,0.4195341132365321,0.5071355294127556,0.7813087218498457,False,3,27,4,4.668973713188908,0.8806570470947873,1.0,1.3051104878964057
|
||||
|
@@ -0,0 +1,46 @@
|
||||
dataset,alpha,seed,beta,n_eligible,n_improve,n_degrade,n_unchanged,mean_delta,min_delta,max_delta
|
||||
xiiotid,0.25,0,0.0,10,0,0,10,0.0,0.0,0.0
|
||||
xiiotid,0.25,0,0.25,10,2,5,3,-0.0064673967169698865,-0.04293419597212661,0.01876993547229222
|
||||
xiiotid,0.25,0,0.5,10,2,7,1,-0.021132734174687993,-0.07692307692307698,0.05741836974395109
|
||||
xiiotid,0.25,0,0.75,10,5,4,1,0.037652802750874605,-0.11166156370194247,0.3758987633016968
|
||||
xiiotid,0.25,0,1.0,10,4,5,1,-0.037995631629473454,-0.25698055252395446,0.14104421200350115
|
||||
xiiotid,0.25,1,0.0,10,0,0,10,0.0,0.0,0.0
|
||||
xiiotid,0.25,1,0.25,10,7,1,2,0.02181236632914685,-0.006350012700025401,0.07175976877899254
|
||||
xiiotid,0.25,1,0.5,10,7,2,1,0.04461512377469677,-0.015820270172650433,0.23562664832014674
|
||||
xiiotid,0.25,1,0.75,10,5,4,1,0.04324763034707273,-0.018266942973367145,0.316706904876871
|
||||
xiiotid,0.25,1,1.0,10,5,4,1,0.0385170238078155,-0.038742745973951775,0.37740563530037213
|
||||
xiiotid,0.25,2,0.0,10,0,0,10,0.0,0.0,0.0
|
||||
xiiotid,0.25,2,0.25,10,5,3,2,-0.024384536677342937,-0.3028515240904621,0.08185020136870569
|
||||
xiiotid,0.25,2,0.5,10,4,4,2,-0.04103939310459288,-0.3397932816537467,0.11851572403806943
|
||||
xiiotid,0.25,2,0.75,10,3,5,2,-0.1176216808834886,-0.6011131725417439,0.12413263414375775
|
||||
xiiotid,0.25,2,1.0,10,3,6,1,-0.1793367342416782,-0.6775352307267201,0.07541312385625187
|
||||
xiiotid,0.5,0,0.0,10,0,0,10,0.0,0.0,0.0
|
||||
xiiotid,0.5,0,0.25,10,9,1,0,0.014447779488805679,-0.0048289738430582485,0.059259259259259345
|
||||
xiiotid,0.5,0,0.5,10,8,2,0,0.02842211408129357,-0.02864627632429495,0.09259259259259256
|
||||
xiiotid,0.5,0,0.75,10,7,3,0,0.020663517144586436,-0.03579795256891627,0.09259259259259256
|
||||
xiiotid,0.5,0,1.0,10,4,6,0,-0.005896451782293366,-0.07604807732022623,0.04139430366632779
|
||||
xiiotid,0.5,1,0.0,10,0,0,10,0.0,0.0,0.0
|
||||
xiiotid,0.5,1,0.25,10,6,2,2,0.007580540867216318,-0.004456876015858091,0.023990860624524046
|
||||
xiiotid,0.5,1,0.5,10,7,2,1,0.016564399764498333,-0.005423903365265936,0.04237609975314893
|
||||
xiiotid,0.5,1,0.75,10,8,1,1,0.026535489229920235,-0.002998819235144723,0.0871872501828449
|
||||
xiiotid,0.5,1,1.0,10,9,0,1,0.054492862707554934,0.0,0.19273339273339285
|
||||
xiiotid,0.5,2,0.0,10,0,0,10,0.0,0.0,0.0
|
||||
xiiotid,0.5,2,0.25,10,7,1,2,0.011191488545697032,-0.0007113366760957973,0.029454054607266078
|
||||
xiiotid,0.5,2,0.5,10,8,0,2,0.02389697185121845,0.0,0.06966444292595181
|
||||
xiiotid,0.5,2,0.75,10,8,1,1,0.05781929956312084,-0.0018572153733706909,0.1770966368667518
|
||||
xiiotid,0.5,2,1.0,10,6,3,1,0.038758776558190745,-0.4028071047074897,0.2675649974447385
|
||||
xiiotid,0.75,0,0.0,10,0,0,10,0.0,0.0,0.0
|
||||
xiiotid,0.75,0,0.25,10,5,5,0,8.859496571733683e-05,-0.019237420306723707,0.026871905512682204
|
||||
xiiotid,0.75,0,0.5,10,6,4,0,0.007584665753678871,-0.0361435910590483,0.048012173012172976
|
||||
xiiotid,0.75,0,0.75,10,3,7,0,-0.009935209564988324,-0.04332234195639206,0.02528490028490027
|
||||
xiiotid,0.75,0,1.0,10,1,9,0,-0.017657004095942678,-0.0650297324550243,0.02220072031392789
|
||||
xiiotid,0.75,1,0.0,10,0,0,10,0.0,0.0,0.0
|
||||
xiiotid,0.75,1,0.25,10,9,0,1,0.01311050414693552,0.0,0.03177895616667353
|
||||
xiiotid,0.75,1,0.5,10,9,0,1,0.014643364516424288,0.0,0.04017223028543784
|
||||
xiiotid,0.75,1,0.75,10,9,0,1,0.0127774748399905,0.0,0.03752345215759845
|
||||
xiiotid,0.75,1,1.0,10,7,2,1,0.011258579628480089,-0.011620820732722359,0.05776636713735561
|
||||
xiiotid,0.75,2,0.0,10,0,0,10,0.0,0.0,0.0
|
||||
xiiotid,0.75,2,0.25,10,7,3,0,-0.005211888340901932,-0.12121212121212133,0.03817567567567559
|
||||
xiiotid,0.75,2,0.5,10,6,4,0,-0.007096659882482407,-0.1523809523809524,0.047814685314685246
|
||||
xiiotid,0.75,2,0.75,10,5,5,0,-0.00033649270926734557,-0.08602150537634423,0.05314748201438846
|
||||
xiiotid,0.75,2,1.0,10,6,4,0,-0.002902966134960444,-0.12121212121212133,0.05314748201438846
|
||||
|
@@ -0,0 +1,136 @@
|
||||
dataset,alpha,class_id,class_name,beta,n_seeds,mean_displacement,std_sample_displacement,mean_relative_displacement
|
||||
xiiotid,0.25,0,C&C,0.0,3,0.0,0.0,0.0
|
||||
xiiotid,0.25,0,C&C,0.25,3,1.27837054967781,0.41822833159420114,0.27003430350349095
|
||||
xiiotid,0.25,0,C&C,0.5,3,2.3990142795607627,0.581298481867443,0.5059337917781374
|
||||
xiiotid,0.25,0,C&C,0.75,3,3.306991238919704,0.508900823524494,0.6970245995294005
|
||||
xiiotid,0.25,0,C&C,1.0,3,4.01952572799183,0.29030488023104745,0.8472326753379348
|
||||
xiiotid,0.25,1,Exfiltration,0.0,3,0.0,0.0,0.0
|
||||
xiiotid,0.25,1,Exfiltration,0.25,3,2.1505748980950266,0.3101835560753807,0.33309243067039757
|
||||
xiiotid,0.25,1,Exfiltration,0.5,3,3.3139866073431565,0.5408774954238195,0.5118900118897919
|
||||
xiiotid,0.25,1,Exfiltration,0.75,3,3.939594030444926,0.7312554933468559,0.6069298415028075
|
||||
xiiotid,0.25,1,Exfiltration,1.0,3,4.316178984369498,0.8975835034935007,0.6638254826227857
|
||||
xiiotid,0.25,2,Exploitation,0.0,3,0.0,0.0,0.0
|
||||
xiiotid,0.25,2,Exploitation,0.25,3,1.1587284531130924,0.36096288681414823,0.23470674175846215
|
||||
xiiotid,0.25,2,Exploitation,0.5,3,2.1283145398223593,0.7573863420735953,0.43060284027932577
|
||||
xiiotid,0.25,2,Exploitation,0.75,3,2.8881691399860485,1.0052398500157818,0.5846207929781134
|
||||
xiiotid,0.25,2,Exploitation,1.0,3,3.464004570499769,1.112779630373774,0.7020410983796918
|
||||
xiiotid,0.25,3,Lateral_movement,0.0,3,0.0,0.0,0.0
|
||||
xiiotid,0.25,3,Lateral_movement,0.25,3,1.983346175953378,0.5729109230595639,0.4196845501731568
|
||||
xiiotid,0.25,3,Lateral_movement,0.5,3,3.0206065448113826,1.0150094706368122,0.639663941527728
|
||||
xiiotid,0.25,3,Lateral_movement,0.75,3,3.500429531100328,1.2632988067241848,0.7415506396377006
|
||||
xiiotid,0.25,3,Lateral_movement,1.0,3,3.7263813611395125,1.3833916615643342,0.7895377723300525
|
||||
xiiotid,0.25,4,Normal,0.0,3,0.0,0.0,0.0
|
||||
xiiotid,0.25,4,Normal,0.25,3,1.0864756872230459,0.496567699923766,0.20451956788647774
|
||||
xiiotid,0.25,4,Normal,0.5,3,1.5767289610073465,0.5644465343832925,0.2945513132600518
|
||||
xiiotid,0.25,4,Normal,0.75,3,1.8318768258260405,0.552047828490767,0.34065176127320745
|
||||
xiiotid,0.25,4,Normal,1.0,3,1.9966341269597232,0.5327206047251788,0.3701992118201333
|
||||
xiiotid,0.25,5,RDOS,0.0,3,0.0,0.0,0.0
|
||||
xiiotid,0.25,5,RDOS,0.25,3,1.0860124145813117,0.4602780439364506,0.13866684735468646
|
||||
xiiotid,0.25,5,RDOS,0.5,3,1.7190552688418272,0.6887072700340696,0.21934364560707523
|
||||
xiiotid,0.25,5,RDOS,0.75,3,2.1822469246461806,0.9474271568645856,0.2787148221815406
|
||||
xiiotid,0.25,5,RDOS,1.0,3,2.5658707936642617,1.2193483512552363,0.3281078404629119
|
||||
xiiotid,0.25,6,Reconnaissance,0.0,3,0.0,0.0,0.0
|
||||
xiiotid,0.25,6,Reconnaissance,0.25,3,1.4788712344122157,0.594533938907045,0.28537388942486464
|
||||
xiiotid,0.25,6,Reconnaissance,0.5,3,2.350247764054481,0.7603933259238349,0.4522079760615029
|
||||
xiiotid,0.25,6,Reconnaissance,0.75,3,2.9233293995154472,0.8953049366648174,0.5612721092899503
|
||||
xiiotid,0.25,6,Reconnaissance,1.0,3,3.3391889586431325,1.1073644700689869,0.6402396428113026
|
||||
xiiotid,0.25,7,Tampering,0.0,3,0.0,0.0,0.0
|
||||
xiiotid,0.25,7,Tampering,0.25,3,1.3505936491446324,0.2586312123810999,0.30342797209829775
|
||||
xiiotid,0.25,7,Tampering,0.5,3,2.5524751358791735,0.4082046541057479,0.5767593796858125
|
||||
xiiotid,0.25,7,Tampering,0.75,3,3.4991562847024547,0.3575352999845257,0.7935853172069489
|
||||
xiiotid,0.25,7,Tampering,1.0,3,4.247813103636777,0.24113229030491104,0.9653304277937593
|
||||
xiiotid,0.25,8,Weaponization,0.0,3,0.0,0.0,0.0
|
||||
xiiotid,0.25,8,Weaponization,0.25,3,1.7105264729761451,0.22286866444144524,0.30652098641043396
|
||||
xiiotid,0.25,8,Weaponization,0.5,3,2.5685181426368175,0.35839871727693023,0.4619957398263043
|
||||
xiiotid,0.25,8,Weaponization,0.75,3,2.951764426805454,0.4937625539064774,0.5317633959257942
|
||||
xiiotid,0.25,8,Weaponization,1.0,3,3.1235303582992926,0.585141395295389,0.5634271266802224
|
||||
xiiotid,0.5,0,C&C,0.0,3,0.0,0.0,0.0
|
||||
xiiotid,0.5,0,C&C,0.25,3,0.6538969764641525,0.2476139923256249,0.12339295466205748
|
||||
xiiotid,0.5,0,C&C,0.5,3,1.118626143061394,0.3963727050225245,0.2105520814834464
|
||||
xiiotid,0.5,0,C&C,0.75,3,1.4486883045785106,0.4772384272097319,0.2724794282105077
|
||||
xiiotid,0.5,0,C&C,1.0,3,1.6935576092145832,0.5048307458168824,0.3187155176777392
|
||||
xiiotid,0.5,1,Exfiltration,0.0,3,0.0,0.0,0.0
|
||||
xiiotid,0.5,1,Exfiltration,0.25,3,0.8338879088602954,0.2741219923879293,0.12284229408877616
|
||||
xiiotid,0.5,1,Exfiltration,0.5,3,1.3517411074356709,0.42853570203269503,0.19904477988621203
|
||||
xiiotid,0.5,1,Exfiltration,0.75,3,1.7154927988410469,0.49900998925508244,0.2524571065984375
|
||||
xiiotid,0.5,1,Exfiltration,1.0,3,2.0204769683934525,0.5020218016853628,0.2973123924755737
|
||||
xiiotid,0.5,2,Exploitation,0.0,3,0.0,0.0,0.0
|
||||
xiiotid,0.5,2,Exploitation,0.25,3,0.6666685285017905,0.18200087099143822,0.12232141909162007
|
||||
xiiotid,0.5,2,Exploitation,0.5,3,1.290546444813813,0.27066503671707776,0.2357165771334672
|
||||
xiiotid,0.5,2,Exploitation,0.75,3,1.85529485339079,0.309252194657293,0.33680609491935254
|
||||
xiiotid,0.5,2,Exploitation,1.0,3,2.343885289699028,0.4121833629248462,0.4231523311819784
|
||||
xiiotid,0.5,3,Lateral_movement,0.0,3,0.0,0.0,0.0
|
||||
xiiotid,0.5,3,Lateral_movement,0.25,3,1.4060488264140794,1.112581110058643,0.1950351203781113
|
||||
xiiotid,0.5,3,Lateral_movement,0.5,3,2.1062819395775434,1.2786883236883044,0.30073851924782274
|
||||
xiiotid,0.5,3,Lateral_movement,0.75,3,2.4882102973029516,1.1721414711156182,0.36273794263869424
|
||||
xiiotid,0.5,3,Lateral_movement,1.0,3,2.7240136758504594,1.0350790616091956,0.40257578575923714
|
||||
xiiotid,0.5,4,Normal,0.0,3,0.0,0.0,0.0
|
||||
xiiotid,0.5,4,Normal,0.25,3,0.7591659420154394,0.32709942089138133,0.1434738312600832
|
||||
xiiotid,0.5,4,Normal,0.5,3,1.1795350343849011,0.4753882408285596,0.2223203173446142
|
||||
xiiotid,0.5,4,Normal,0.75,3,1.4114463532549024,0.5293831411155098,0.2653104861812456
|
||||
xiiotid,0.5,4,Normal,1.0,3,1.557331074720638,0.5480258187545208,0.2920883603702228
|
||||
xiiotid,0.5,5,RDOS,0.0,3,0.0,0.0,0.0
|
||||
xiiotid,0.5,5,RDOS,0.25,3,1.2054779842601517,0.7293986290124911,0.16305203219584322
|
||||
xiiotid,0.5,5,RDOS,0.5,3,1.8233255406714963,0.9982539168312503,0.24557116018390387
|
||||
xiiotid,0.5,5,RDOS,0.75,3,2.258386664022743,1.1111681429896514,0.3031764701965988
|
||||
xiiotid,0.5,5,RDOS,1.0,3,2.6312389613743776,1.1651317404804817,0.3523347102777825
|
||||
xiiotid,0.5,6,Reconnaissance,0.0,3,0.0,0.0,0.0
|
||||
xiiotid,0.5,6,Reconnaissance,0.25,3,0.32567775116244774,0.11787216678901793,0.055493937112848946
|
||||
xiiotid,0.5,6,Reconnaissance,0.5,3,0.6024083113978019,0.19509381934930423,0.10221941764104735
|
||||
xiiotid,0.5,6,Reconnaissance,0.75,3,0.8264969491723915,0.24209312478661804,0.13974777812154845
|
||||
xiiotid,0.5,6,Reconnaissance,1.0,3,1.00151995809175,0.26099624924542353,0.16884924727680906
|
||||
xiiotid,0.5,7,Tampering,0.0,3,0.0,0.0,0.0
|
||||
xiiotid,0.5,7,Tampering,0.25,3,0.6958022407930811,0.08690380480265254,0.14078908166802012
|
||||
xiiotid,0.5,7,Tampering,0.5,3,1.3112838021058792,0.35103438443835877,0.26700132395623627
|
||||
xiiotid,0.5,7,Tampering,0.75,3,1.8761038090972573,0.7753681393042942,0.3837387923644013
|
||||
xiiotid,0.5,7,Tampering,1.0,3,2.354018138564271,1.165407725687578,0.48267240310142356
|
||||
xiiotid,0.5,8,Weaponization,0.0,3,0.0,0.0,0.0
|
||||
xiiotid,0.5,8,Weaponization,0.25,3,0.8836150972431183,0.469653346490459,0.15212044699184105
|
||||
xiiotid,0.5,8,Weaponization,0.5,3,1.5842620542218915,0.7696695063647051,0.2703303067352452
|
||||
xiiotid,0.5,8,Weaponization,0.75,3,2.141052662540764,1.025083084023739,0.36329011806065653
|
||||
xiiotid,0.5,8,Weaponization,1.0,3,2.560790423872144,1.2282783431433644,0.4334295567239335
|
||||
xiiotid,0.75,0,C&C,0.0,3,0.0,0.0,0.0
|
||||
xiiotid,0.75,0,C&C,0.25,3,0.439241829432576,0.2482668440171278,0.08997758594748201
|
||||
xiiotid,0.75,0,C&C,0.5,3,0.7678410072672376,0.3909965913837135,0.15701946966810795
|
||||
xiiotid,0.75,0,C&C,0.75,3,1.0410848664700902,0.4814392749891062,0.21255529764935774
|
||||
xiiotid,0.75,0,C&C,1.0,3,1.2839465030740465,0.5431989970423492,0.2617816727650299
|
||||
xiiotid,0.75,1,Exfiltration,0.0,3,0.0,0.0,0.0
|
||||
xiiotid,0.75,1,Exfiltration,0.25,3,0.6096329492397241,0.15529587518313812,0.08815738333426759
|
||||
xiiotid,0.75,1,Exfiltration,0.5,3,0.9900899725245896,0.15059193858817135,0.1423829525956932
|
||||
xiiotid,0.75,1,Exfiltration,0.75,3,1.2536544998955659,0.10576760245352612,0.17957488577930802
|
||||
xiiotid,0.75,1,Exfiltration,1.0,3,1.4475761921343262,0.08598433748869257,0.20679504552799255
|
||||
xiiotid,0.75,2,Exploitation,0.0,3,0.0,0.0,0.0
|
||||
xiiotid,0.75,2,Exploitation,0.25,3,0.4576570034781726,0.128934732252835,0.08525019886525016
|
||||
xiiotid,0.75,2,Exploitation,0.5,3,0.8504289045197803,0.09539544332992135,0.15761005429469221
|
||||
xiiotid,0.75,2,Exploitation,0.75,3,1.2085539298827332,0.04564296145945021,0.22330324296750917
|
||||
xiiotid,0.75,2,Exploitation,1.0,3,1.5392602070293495,0.25171201225922846,0.2839417733897609
|
||||
xiiotid,0.75,3,Lateral_movement,0.0,3,0.0,0.0,0.0
|
||||
xiiotid,0.75,3,Lateral_movement,0.25,3,0.5461495626298819,0.3229980967371187,0.10516299618218877
|
||||
xiiotid,0.75,3,Lateral_movement,0.5,3,0.9115139836526881,0.4493586574794453,0.1749147577856791
|
||||
xiiotid,0.75,3,Lateral_movement,0.75,3,1.1750905945007586,0.5128745337831714,0.22498947669980307
|
||||
xiiotid,0.75,3,Lateral_movement,1.0,3,1.3693216274264168,0.5527158531960167,0.2618053240393338
|
||||
xiiotid,0.75,4,Normal,0.0,3,0.0,0.0,0.0
|
||||
xiiotid,0.75,4,Normal,0.25,3,0.3154682998030463,0.10443504134088931,0.056799260146204594
|
||||
xiiotid,0.75,4,Normal,0.5,3,0.5587470690472488,0.17823349266094118,0.10039903187569306
|
||||
xiiotid,0.75,4,Normal,0.75,3,0.7490874520257846,0.23967850866469875,0.13441982891499835
|
||||
xiiotid,0.75,4,Normal,1.0,3,0.9031246281714095,0.298425213658255,0.1619501084487235
|
||||
xiiotid,0.75,5,RDOS,0.0,3,0.0,0.0,0.0
|
||||
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"support_cv_mean": 1.4559013516894272,
|
||||
"support_max_min_ratio_max": 46541.0,
|
||||
"union_rare_count": 8,
|
||||
"union_unseen_count": 5
|
||||
}
|
||||
],
|
||||
"seeds": [
|
||||
0,
|
||||
1,
|
||||
2
|
||||
],
|
||||
"summary": "/home/willtanoe/projects/perdalam-protean/artifacts/analysis/xiiotid__cross_alpha__partition_heterogeneity_summary.csv",
|
||||
"summary_rows": [
|
||||
{
|
||||
"alpha": 0.75,
|
||||
"cells_sj_lt_M_total": 3,
|
||||
"cells_total": 27,
|
||||
"client_size_ratio_max": 5.07283910650696,
|
||||
"client_size_ratio_mean": 4.668973713188908,
|
||||
"dataset": "xiiotid",
|
||||
"max_unseen_on_client": 1,
|
||||
"missing_client_class_cells_total": 4,
|
||||
"n_seeds": 3,
|
||||
"support_cv_mean": 0.8806570470947873,
|
||||
"support_max_min_ratio_max": 1903.0,
|
||||
"union_rare_mean": 5.0,
|
||||
"union_unseen_mean": 1.0
|
||||
},
|
||||
{
|
||||
"alpha": 0.5,
|
||||
"cells_sj_lt_M_total": 7,
|
||||
"cells_total": 27,
|
||||
"client_size_ratio_max": 9.890694678426321,
|
||||
"client_size_ratio_mean": 7.405360903230798,
|
||||
"dataset": "xiiotid",
|
||||
"max_unseen_on_client": 2,
|
||||
"missing_client_class_cells_total": 9,
|
||||
"n_seeds": 3,
|
||||
"support_cv_mean": 1.1833344484214374,
|
||||
"support_max_min_ratio_max": 12215.0,
|
||||
"union_rare_mean": 6.666666666666667,
|
||||
"union_unseen_mean": 2.3333333333333335
|
||||
},
|
||||
{
|
||||
"alpha": 0.25,
|
||||
"cells_sj_lt_M_total": 19,
|
||||
"cells_total": 27,
|
||||
"client_size_ratio_max": 20.837033843500755,
|
||||
"client_size_ratio_mean": 14.745270966890343,
|
||||
"dataset": "xiiotid",
|
||||
"max_unseen_on_client": 4,
|
||||
"missing_client_class_cells_total": 38,
|
||||
"n_seeds": 3,
|
||||
"support_cv_mean": 1.4423832412721973,
|
||||
"support_max_min_ratio_max": 122800.0,
|
||||
"union_rare_mean": 7.666666666666667,
|
||||
"union_unseen_mean": 5.666666666666667
|
||||
}
|
||||
]
|
||||
}
|
||||
@@ -0,0 +1,82 @@
|
||||
dataset,alpha,seed,class_id,class_name,total,num_clients,n_missing_clients,min,max,mean,std,cv,max_min_ratio
|
||||
xiiotid,0.75,0,0,C&C,2004,8,2,5,760,250.5,222.37468381090505,0.8877232886662877,152.0
|
||||
xiiotid,0.75,0,1,Exfiltration,15494,10,0,27,4392,1549.4,1310.2802143053218,0.8456694296536219,162.66666666666666
|
||||
xiiotid,0.75,0,2,Exploitation,793,9,1,1,240,88.11111111111111,77.07347784844227,0.8747305178259526,240.0
|
||||
xiiotid,0.75,0,3,Lateral_movement,22117,10,0,190,5435,2211.7,1964.874960398244,0.8884003076358656,28.605263157894736
|
||||
xiiotid,0.75,0,4,Normal,292777,10,0,1151,92460,29277.7,26706.460263576675,0.9121775366089779,80.33014769765421
|
||||
xiiotid,0.75,0,5,RDOS,98883,10,0,347,22821,9888.3,7609.664802736058,0.7695624933240354,65.76657060518733
|
||||
xiiotid,0.75,0,6,Reconnaissance,89161,10,0,458,23824,8916.1,8755.430559943925,0.9819798521712323,52.0174672489083
|
||||
xiiotid,0.75,0,7,Tampering,3586,10,0,31,1227,358.6,421.7822186863737,1.1761913516072886,39.58064516129032
|
||||
xiiotid,0.75,0,8,Weaponization,45094,10,0,285,12915,4509.4,4085.1338337929637,0.9059151625034293,45.31578947368421
|
||||
xiiotid,0.75,1,0,C&C,2004,9,1,87,538,222.66666666666666,136.2049109899411,0.6116987020506338,6.183908045977011
|
||||
xiiotid,0.75,1,1,Exfiltration,15494,10,0,239,3749,1549.4,1362.2074878666613,0.8791838697990585,15.686192468619247
|
||||
xiiotid,0.75,1,2,Exploitation,793,10,0,4,246,79.3,79.05320992850321,0.9968878931715411,61.5
|
||||
xiiotid,0.75,1,3,Lateral_movement,22117,10,0,556,4082,2211.7,1317.6872959849009,0.5957803029275675,7.341726618705036
|
||||
xiiotid,0.75,1,4,Normal,292777,10,0,4311,73956,29277.7,23958.28045186048,0.8183115631303168,17.15518441196938
|
||||
xiiotid,0.75,1,5,RDOS,98883,10,0,268,34051,9888.3,9256.126976765176,0.9360685837570842,127.05597014925372
|
||||
xiiotid,0.75,1,6,Reconnaissance,89161,10,0,520,22127,8916.1,6960.1977335417705,0.7806325336797221,42.551923076923075
|
||||
xiiotid,0.75,1,7,Tampering,3586,10,0,25,1004,358.6,307.1879554930499,0.8566312200029278,40.16
|
||||
xiiotid,0.75,1,8,Weaponization,45094,10,0,269,10726,4509.4,3590.911199124813,0.7963168490541565,39.87360594795539
|
||||
xiiotid,0.75,2,0,C&C,2004,10,0,1,546,200.4,183.81414526635322,0.9172362538241179,546.0
|
||||
xiiotid,0.75,2,1,Exfiltration,15494,10,0,9,3572,1549.4,1333.091834796088,0.8603923033407048,396.8888888888889
|
||||
xiiotid,0.75,2,2,Exploitation,793,10,0,11,382,79.3,104.84374087183268,1.3221152695060867,34.72727272727273
|
||||
xiiotid,0.75,2,3,Lateral_movement,22117,10,0,3,5709,2211.7,1943.4331503810467,0.8787055886336514,1903.0
|
||||
xiiotid,0.75,2,4,Normal,292777,10,0,1930,64353,29277.7,23149.92923984866,0.7907017709672776,33.343523316062175
|
||||
xiiotid,0.75,2,5,RDOS,98883,10,0,636,18655,9888.3,5578.985284977905,0.5642006497555602,29.33176100628931
|
||||
xiiotid,0.75,2,6,Reconnaissance,89161,10,0,1528,21418,8916.1,6174.089899734211,0.692465304307288,14.017015706806284
|
||||
xiiotid,0.75,2,7,Tampering,3586,10,0,1,1321,358.6,398.6803732314898,1.1117690274163128,1321.0
|
||||
xiiotid,0.75,2,8,Weaponization,45094,10,0,169,17328,4509.4,5078.904058948151,1.1262926462385576,102.53254437869822
|
||||
xiiotid,0.5,0,0,C&C,2004,10,0,1,966,200.4,301.01302297408995,1.5020609928846804,966.0
|
||||
xiiotid,0.5,0,1,Exfiltration,15494,9,1,45,6305,1721.5555555555557,1785.267369400705,1.0370082822128788,140.11111111111111
|
||||
xiiotid,0.5,0,2,Exploitation,793,8,2,10,353,99.125,107.69451877881251,1.0864516396349306,35.3
|
||||
xiiotid,0.5,0,3,Lateral_movement,22117,10,0,49,8385,2211.7,2692.423482663899,1.217354741901659,171.12244897959184
|
||||
xiiotid,0.5,0,4,Normal,292777,10,0,604,68657,29277.7,22396.371889437807,0.7649635008705535,113.6705298013245
|
||||
xiiotid,0.5,0,5,RDOS,98883,10,0,168,49283,9888.3,13609.872137900486,1.3763611680370222,293.3511904761905
|
||||
xiiotid,0.5,0,6,Reconnaissance,89161,10,0,1137,29234,8916.1,10378.249413557183,1.1639897952644298,25.711521547933156
|
||||
xiiotid,0.5,0,7,Tampering,3586,9,1,2,1266,398.44444444444446,396.92067808487633,0.996175711869461,633.0
|
||||
xiiotid,0.5,0,8,Weaponization,45094,10,0,18,32409,4509.4,9448.019678218288,2.0951833233286665,1800.5
|
||||
xiiotid,0.5,1,0,C&C,2004,8,2,2,687,250.5,246.01270292405636,0.9820866384193867,343.5
|
||||
xiiotid,0.5,1,1,Exfiltration,15494,10,0,8,6273,1549.4,1811.7618607311504,1.169331264186879,784.125
|
||||
xiiotid,0.5,1,2,Exploitation,793,9,1,1,491,88.11111111111111,144.76758725967514,1.6430117091261995,491.0
|
||||
xiiotid,0.5,1,3,Lateral_movement,22117,10,0,49,8361,2211.7,2542.799797467351,1.1497037561456576,170.6326530612245
|
||||
xiiotid,0.5,1,4,Normal,292777,10,0,260,89253,29277.7,30294.75088542568,1.0347380731896865,343.28076923076924
|
||||
xiiotid,0.5,1,5,RDOS,98883,10,0,6,47276,9888.3,14002.426425802065,1.4160600331504976,7879.333333333333
|
||||
xiiotid,0.5,1,6,Reconnaissance,89161,10,0,1842,23967,8916.1,6441.9730432531305,0.72251018306806,13.011400651465799
|
||||
xiiotid,0.5,1,7,Tampering,3586,9,1,8,1228,398.44444444444446,373.67279540353394,0.9378291016820428,153.5
|
||||
xiiotid,0.5,1,8,Weaponization,45094,10,0,917,11526,4509.4,4011.2644440375657,0.8895339610674515,12.569247546346784
|
||||
xiiotid,0.5,2,0,C&C,2004,9,1,13,576,222.66666666666666,158.27683202400647,0.7108240959161968,44.30769230769231
|
||||
xiiotid,0.5,2,1,Exfiltration,15494,10,0,20,5300,1549.4,1486.1657511865894,0.9591879122154313,265.0
|
||||
xiiotid,0.5,2,2,Exploitation,793,10,0,1,298,79.3,104.09615746990855,1.3126879882712301,298.0
|
||||
xiiotid,0.5,2,3,Lateral_movement,22117,10,0,11,6341,2211.7,2001.0836089479121,0.90477171811182,576.4545454545455
|
||||
xiiotid,0.5,2,4,Normal,292777,10,0,79,92031,29277.7,32244.598171011534,1.1013364496190456,1164.9493670886077
|
||||
xiiotid,0.5,2,5,RDOS,98883,10,0,4,48860,9888.3,14020.836187973955,1.4179218053633038,12215.0
|
||||
xiiotid,0.5,2,6,Reconnaissance,89161,10,0,208,22975,8916.1,7703.846681366394,0.8640377161950172,110.45673076923077
|
||||
xiiotid,0.5,2,7,Tampering,3586,10,0,26,2437,358.6,698.4746523675716,1.9477820757600992,93.73076923076923
|
||||
xiiotid,0.5,2,8,Weaponization,45094,10,0,17,23228,4509.4,6976.612103306303,1.5471264698865266,1366.3529411764705
|
||||
xiiotid,0.25,0,0,C&C,2004,10,0,21,1065,200.4,296.149691878955,1.4777928736474801,50.714285714285715
|
||||
xiiotid,0.25,0,1,Exfiltration,15494,8,2,4,7950,1936.75,2720.187390144289,1.4045113670552674,1987.5
|
||||
xiiotid,0.25,0,2,Exploitation,793,6,4,2,595,132.16666666666666,208.87669142875237,1.5804037182503332,297.5
|
||||
xiiotid,0.25,0,3,Lateral_movement,22117,9,1,2,13857,2457.4444444444443,4448.236282470993,1.8101065489098402,6928.5
|
||||
xiiotid,0.25,0,4,Normal,292777,10,0,1,122800,29277.7,39398.78122239316,1.3456924971016562,122800.0
|
||||
xiiotid,0.25,0,5,RDOS,98883,10,0,166,31089,9888.3,10684.255463531374,1.080494671837563,187.28313253012047
|
||||
xiiotid,0.25,0,6,Reconnaissance,89161,8,2,46,65307,11145.125,20676.50504460014,1.8552062040219504,1419.7173913043478
|
||||
xiiotid,0.25,0,7,Tampering,3586,8,2,9,2272,448.25,703.1018329516713,1.5685484282245874,252.44444444444446
|
||||
xiiotid,0.25,0,8,Weaponization,45094,8,2,43,23381,5636.75,8611.380141272362,1.527720786139595,543.7441860465116
|
||||
xiiotid,0.25,1,0,C&C,2004,9,1,1,986,222.66666666666666,347.19286987046394,1.559249415585916,986.0
|
||||
xiiotid,0.25,1,1,Exfiltration,15494,10,0,1,6204,1549.4,1918.3846955186025,1.238146828139023,6204.0
|
||||
xiiotid,0.25,1,2,Exploitation,793,8,2,1,321,99.125,128.38558865776173,1.2951887884767892,321.0
|
||||
xiiotid,0.25,1,3,Lateral_movement,22117,10,0,1,10094,2211.7,3172.3787305427454,1.4343621334461027,10094.0
|
||||
xiiotid,0.25,1,4,Normal,292777,8,2,198,129678,36597.125,42579.4751242823,1.16346502967876,654.939393939394
|
||||
xiiotid,0.25,1,5,RDOS,98883,9,1,168,53482,10987.0,16131.251346377318,1.4682125554179775,318.3452380952381
|
||||
xiiotid,0.25,1,6,Reconnaissance,89161,8,2,138,65101,11145.125,20636.12875176386,1.8515834278901186,471.7463768115942
|
||||
xiiotid,0.25,1,7,Tampering,3586,9,1,2,1804,398.44444444444446,536.9212876537887,1.3475436667273,902.0
|
||||
xiiotid,0.25,1,8,Weaponization,45094,9,1,1,12024,5010.444444444444,4173.732332127554,0.8330064085942251,12024.0
|
||||
xiiotid,0.25,2,0,C&C,2004,6,4,2,1265,334.0,439.2504980076858,1.3151212515200172,632.5
|
||||
xiiotid,0.25,2,1,Exfiltration,15494,8,2,4,8269,1936.75,2589.4560118874388,1.3370109781269852,2067.25
|
||||
xiiotid,0.25,2,2,Exploitation,793,6,4,1,485,132.16666666666666,175.5395650242101,1.3281682095148306,485.0
|
||||
xiiotid,0.25,2,3,Lateral_movement,22117,7,3,1,12496,3159.5714285714284,4660.178716902324,1.4749401373747013,12496.0
|
||||
xiiotid,0.25,2,4,Normal,292777,9,1,452,118937,32530.777777777777,35898.97737255285,1.1035388584245882,263.13495575221236
|
||||
xiiotid,0.25,2,5,RDOS,98883,10,0,2,48839,9888.3,14049.173043634988,1.4207875007468411,24419.5
|
||||
xiiotid,0.25,2,6,Reconnaissance,89161,10,0,1,46541,8916.1,13537.102034408988,1.5182761559884914,46541.0
|
||||
xiiotid,0.25,2,7,Tampering,3586,10,0,1,2584,358.6,765.2960472915041,2.1341217158156836,2584.0
|
||||
xiiotid,0.25,2,8,Weaponization,45094,9,1,4,22853,5010.444444444444,7371.102105310547,1.4711473576927068,5713.25
|
||||
|
@@ -0,0 +1,10 @@
|
||||
dataset,alpha,seed,num_clients,num_classes,num_train,nij_sum,n_class_condition_cells,n_cells_sj_lt_M,n_missing_client_class_cells,client_size_min,client_size_max,client_size_ratio,union_rare_count,union_unseen_count,max_unseen_on_client,n_clients_2_rare,support_cv_mean,support_cv_max,support_max_min_ratio_max,manifest_content_hash,partition_hash,split_hash,rng_seed
|
||||
xiiotid,0.75,0,10,9,569909,569909,9,2,3,24236,100573,4.149735930021456,4,2,1,10,0.9158166599996324,1.1761913516072886,240.0,759f7e504a7d442101238726334d121a746ea4a8ff366428c1c174e47f358723,473b1c4aaaa9e55e5cc2d108a261345e6630fe481630987df60a5ac30f793048,d0acc0c14e3ecbeba02dfa9e6227c983da12dec2d6111df0b714002e6e03c29d,957653162
|
||||
xiiotid,0.75,1,10,9,569909,569909,9,1,1,21623,109690,5.07283910650696,5,1,1,10,0.8079457241747787,0.9968878931715411,127.05597014925372,4a50ba219de20af14f6ad73976111659fba2d5b25cd5eeb1a2f21b76de0d9303,a0ec9e9c0902c64b12bbfdb2c2ec1ee814a83699b2d48c88b7edd6255aa90022,880a9f82686bbf3af83880238aeef6f1462881ba87c5ae667b7415eb10d79892,762050403
|
||||
xiiotid,0.75,2,10,9,569909,569909,9,0,0,24224,115896,4.784346103038309,6,0,0,10,0.9182087571099508,1.3221152695060867,1903.0,922b7bb15169302be7dd4d4eb1644d077537872e1e91fe59b7525b7e3343cc1c,00345255053affa05ebf348cee3efd6dc85ede6c4e500de881b9d96605d99b0e,8e0db0be53055317b4df53398fad500c1a3f09491967539bf5459ba5600cee09,843543396
|
||||
xiiotid,0.5,0,10,9,569909,569909,9,3,4,18521,94564,5.105771826575239,6,3,2,10,1.248838795111587,2.0951833233286665,1800.5,e81a6538ecefcda202aa7602310ff8d8c9529031ab9dcbec4ebbabc0e63b636c,2465485539a3e923548dcc0c73d8acc5076d456536b78682d512897ea586e779,d0acc0c14e3ecbeba02dfa9e6227c983da12dec2d6111df0b714002e6e03c29d,2009062324
|
||||
xiiotid,0.5,1,10,9,569909,569909,9,3,4,16884,121896,7.219616204690832,7,3,2,10,1.1049783022262067,1.6430117091261995,7879.333333333333,54ea1df16a2e7998cc21c3cee86318dc02a2fd8396894371ebaab7f87bad7e98,4061c5a15ff5c981cb0ae90beb892ad2ef730fb460a995d80fcef77bbcba52a3,880a9f82686bbf3af83880238aeef6f1462881ba87c5ae667b7415eb10d79892,621679668
|
||||
xiiotid,0.5,2,10,9,569909,569909,9,1,1,10091,99807,9.890694678426321,7,1,1,10,1.1961862479265188,1.9477820757600992,12215.0,be881ac63bc0057eca7c82d762d082344e1f4fbd1dff56a475898c6de977712a,1118e7fa4e7d852e38b1b8a6e2789c5c6e357579698de7497a4436d02869e214,8e0db0be53055317b4df53398fad500c1a3f09491967539bf5459ba5600cee09,1438483982
|
||||
xiiotid,0.25,0,10,9,569909,569909,9,6,13,9075,141358,15.576639118457301,8,6,3,10,1.5167196772431413,1.8552062040219504,122800.0,839ba18e2d87245d198be8f5f89d4a24f13cdb6fc64c004d406c6d4f8246f3da,60faf299c0220bb6dd013fd4621babe8f6ad342e3012b983bce11445252a2b21,d0acc0c14e3ecbeba02dfa9e6227c983da12dec2d6111df0b714002e6e03c29d,1617371214
|
||||
xiiotid,0.25,1,10,9,569909,569909,9,7,10,9278,193326,20.837033843500755,7,6,4,10,1.3545286948840236,1.8515834278901186,12024.0,84c20b4bd6cd20010fa35d139a0416cb06e79c82fbd8e1d57441cafdcdfbf15d,6ffb10aec991b9d440bad675b72f07d0807c73fa334f86b284eeb90df31687aa,880a9f82686bbf3af83880238aeef6f1462881ba87c5ae667b7415eb10d79892,1670706564
|
||||
xiiotid,0.25,2,10,9,569909,569909,9,6,15,15664,122526,7.822139938712972,8,5,3,10,1.4559013516894272,2.1341217158156836,46541.0,d6e68ee13cb11f98cfb4aea668f3e905d3ebc94884632352c0045fc5f86df28c,c8e1ad316272b858d61b083cd65a174ed674f37157c24d06efb713960b710996,8e0db0be53055317b4df53398fad500c1a3f09491967539bf5459ba5600cee09,795318573
|
||||
|
@@ -0,0 +1,4 @@
|
||||
dataset,alpha,n_seeds,cells_sj_lt_M_total,cells_total,missing_client_class_cells_total,client_size_ratio_mean,client_size_ratio_max,union_unseen_mean,max_unseen_on_client,union_rare_mean,support_cv_mean,support_max_min_ratio_max
|
||||
xiiotid,0.75,3,3,27,4,4.668973713188908,5.07283910650696,1.0,1,5.0,0.8806570470947873,1903.0
|
||||
xiiotid,0.5,3,7,27,9,7.405360903230798,9.890694678426321,2.3333333333333335,2,6.666666666666667,1.1833344484214374,12215.0
|
||||
xiiotid,0.25,3,19,27,38,14.745270966890343,20.837033843500755,5.666666666666667,4,7.666666666666667,1.4423832412721973,122800.0
|
||||
|
+242
-221
@@ -3,34 +3,33 @@
|
||||
This is the canonical continuation point for the next agent session. It is written to be
|
||||
readable without prior chat history, terminal scrollback, or git history.
|
||||
|
||||
Last updated: 2026-09-26 (Session 7, post-experiment audit complete). Session 7 type:
|
||||
**protocol-scaling / non-IID-severity experiment**. Session 6 completed X-IIoTID `alpha=0.50`
|
||||
for seeds `{0,1,2}`. Session 7 completed X-IIoTID **`alpha=0.25`** for seeds `{0,1,2}` across
|
||||
the five frozen beta candidates plus `original_protean`, using the **same pooled-across-seed
|
||||
validation-only** selection rule. **alpha=0.75 and 5G-NIDD were not run.** No commit or push
|
||||
was made.
|
||||
Last updated: 2026-09-26 (Session 8). Session 8 type: **protocol-scaling /
|
||||
non-IID-severity experiment**. Session 7 completed X-IIoTID `alpha=0.25`; Session 6 completed
|
||||
`alpha=0.50`. Session 8 completed X-IIoTID **`alpha=0.75`** for seeds `{0,1,2}` across the five
|
||||
frozen beta candidates plus `original_protean`, using the **same pooled-across-seed
|
||||
validation-only** selection rule, and produced the first **three-alpha (0.25/0.50/0.75)
|
||||
comparison** for X-IIoTID. **5G-NIDD was not run.** No commit or push was made.
|
||||
|
||||
> **Audit status (Session 7).** Independent audit verdict: **PASS WITH MINOR CORRECTIONS**
|
||||
> (`docs/research/SESSION7_AUDIT.md`). `beta_star(alpha=0.25) = 0.00` confirmed from validation
|
||||
> only; leakage audit PASS; `beta=0` class **B**; source/data integrity PASS; pytest 75 passed,
|
||||
> 0 failed, 0 skipped, 0 warnings. Corrections were documentation-only (cross-alpha label
|
||||
> disambiguation + one wording nuance); no `beta_star` or scientific interpretation changed.
|
||||
> **Session 7 is safe to checkpoint.**
|
||||
> **Audit status (Session 8).** Independent audit verdict: **PASS** (`docs/research/SESSION8_AUDIT.md`).
|
||||
> `beta_star(alpha=0.75) = 0.50` confirmed from validation only; no corrections required; run
|
||||
> inventory 18/18; pairing hash-identical and reproduced from raw data; leakage audit PASS;
|
||||
> `beta=0` class **B**; source/data integrity PASS; pytest 75 passed. **Session 8 is safe to
|
||||
> checkpoint.**
|
||||
|
||||
> **Headline (Session 7).** PRIMARY pooled-validation selected beta for X-IIoTID
|
||||
> `alpha=0.25` = **0.00** (validation only). The pooled validation curve is monotonically
|
||||
> **decreasing** in beta at alpha=0.25, whereas at alpha=0.50 it peaked at 0.75. Per-seed
|
||||
> diagnostics were 0.75 / 0.50 / 0.00. beta=0 is class **B** (semantically equivalent +
|
||||
> floating-point divergence) for all three seeds; no semantic discrepancy. The realized
|
||||
> alpha=0.25 partitions are materially more heterogeneous (19/27 class-condition cells with
|
||||
> `|S_j| < M` vs 7/27 at alpha=0.50). Effect remains small relative to between-seed variance.
|
||||
> **Headline (Session 8).** PRIMARY pooled-validation selected beta for X-IIoTID `alpha=0.75`
|
||||
> = **0.50** (validation only; per-seed diagnostics 0.50 / 0.50 / 0.00). The pooled validation
|
||||
> curve peaks at 0.50 and declines both sides, but the total between-beta spread (≈ 0.0081) is
|
||||
> much smaller than the between-seed std (≈ 0.045). `beta=0` is class **B** for all three seeds.
|
||||
> Realized alpha=0.75 partitions are the mildest of the three (3/27 cells with `|S_j| < M`,
|
||||
> 4 missing cells, client-ratio mean 4.67). **Three-alpha pooled selections: 0.25 → 0.00,
|
||||
> 0.50 → 0.75, 0.75 → 0.50 — not monotone in alpha.**
|
||||
|
||||
---
|
||||
|
||||
## 1. Project objective
|
||||
|
||||
Build the code and experiment infrastructure for a thesis study that modifies **only the
|
||||
server-side prototype aggregation** of PROTEAN (Chennoufi et al., 2025), a federated
|
||||
Build the code and experiment infrastructure for a thesis study that modifies **only** the
|
||||
server-side prototype aggregation of PROTEAN (Chennoufi et al., 2025), a federated
|
||||
intrusion-detection framework. The mechanism weights each contributing client's class
|
||||
prototype by its class sample support:
|
||||
|
||||
@@ -55,327 +54,350 @@ bitwise identical to the baseline (see §7).
|
||||
`~/datasets/5G-NIDD/5G-NIDD.csv`
|
||||
`fa36f80859585f474504ca69eb951a079b35145537976c86b00aae3aab46ee59`.
|
||||
- Frozen baseline (`original_protean`) source unchanged; no `equal_available` mode added;
|
||||
beta candidate set unchanged (`{0, .25, .5, .75, 1}`).
|
||||
beta candidate set unchanged (`{0, .25, .5, .75, 1}`). No tracked source/test/config file
|
||||
differs from HEAD.
|
||||
|
||||
## 3. Session 7 objective and outcome
|
||||
## 3. Session 8 objective and outcome
|
||||
|
||||
Objective: evaluate one additional non-IID severity (X-IIoTID `alpha=0.25`, seeds `{0,1,2}`)
|
||||
across the five beta candidates using the exact Session-6 three-seed pooled-validation
|
||||
protocol, and test whether the pooled-selected beta changes under a more heterogeneous
|
||||
condition. All 18 runs (15 `support_weighted` + 3 `original_protean`) completed with rc=0.
|
||||
Report: `docs/research/ALPHA025_BETA_VALIDATION.md`.
|
||||
Objective: evaluate the final X-IIoTID non-IID severity (`alpha=0.75`, seeds `{0,1,2}`) across
|
||||
the five beta candidates using the exact pooled-validation protocol, then compare alpha=0.25,
|
||||
0.50 and 0.75 using realized partition characteristics. All 18 runs (15 `support_weighted` +
|
||||
3 `original_protean`) completed with rc=0.
|
||||
|
||||
Outcome: **PRIMARY pooled-validation selected beta = 0.00** (validation only);
|
||||
`test_used_for_selection = false` for all 15 support_weighted runs. Pooled means: 0.00 →
|
||||
0.591704, 0.25 → 0.588691, 0.50 → 0.585851, 0.75 → 0.579463, 1.00 → 0.532099 (monotone
|
||||
decreasing). Between-seed std 0.045–0.090; the effect is small relative to seed variance.
|
||||
Outcome: **PRIMARY pooled-validation selected beta = 0.50** (validation only);
|
||||
`test_used_for_selection = false` for all 15 runs. Pooled means: 0.00 → 0.471706,
|
||||
0.25 → 0.474368, 0.50 → 0.476749, 0.75 → 0.472541, 1.00 → 0.468605 (peak at 0.50). Between-seed
|
||||
std 0.0447–0.0553; between-beta spread ≈ 0.0081, so the effect is small relative to seed
|
||||
variance.
|
||||
|
||||
Reports: `docs/research/ALPHA075_BETA_VALIDATION.md`,
|
||||
`docs/research/XIIOTID_CROSS_ALPHA_ANALYSIS.md`, audit `docs/research/SESSION8_AUDIT.md`.
|
||||
|
||||
## 4. Condition and pairing
|
||||
|
||||
| Field | Value |
|
||||
|---|---|
|
||||
| dataset / alpha / seeds | `xiiotid` / 0.25 / `{0,1,2}` |
|
||||
| dataset / alpha / seeds | `xiiotid` / 0.75 / `{0,1,2}` |
|
||||
| runs | 15 `support_weighted` + 3 `original_protean`, all new this session |
|
||||
| training | 10 clients, 10 rounds, 3 local epochs, batch 256, lr 1e-3, mu 0.1, lambda 1.0, Adam |
|
||||
| code revision | unchanged from HEAD `6b97a0d38b839c737c49f41006817503d0672871`; only docs/analysis artifacts added |
|
||||
| code revision | unchanged from HEAD `ff68d380e23859d21c07c8a3a7b56b1b7f06c91b`; only docs/analysis/scripts added |
|
||||
|
||||
Manifests (reused, never regenerated; one content hash per seed across all six runs; each was
|
||||
reproduced from the raw dataset with split/`N_ij`/partition hashes verified):
|
||||
Manifests (reused, never regenerated; one content hash per seed across all six runs; each
|
||||
reproduced from the raw dataset with split/`N_ij`/partition hash verified):
|
||||
|
||||
| seed | manifest | content hash | partition hash | split hash | rng seed |
|
||||
|---|---|---|---|---|---|
|
||||
| 0 | `artifacts/partitions/xiiotid__alpha0.25__seed0.json` | `839ba18e…` | `60faf299…` | `d0acc0c1…` | 1617371214 |
|
||||
| 1 | `artifacts/partitions/xiiotid__alpha0.25__seed1.json` | `84c20b4b…` | `6ffb10ae…` | `880a9f82…` | 1670706564 |
|
||||
| 2 | `artifacts/partitions/xiiotid__alpha0.25__seed2.json` | `d6e68ee1…` | `c8e1ad31…` | `8e0db0be…` | 795318573 |
|
||||
| 0 | `artifacts/partitions/xiiotid__alpha0.75__seed0.json` | `759f7e50…` | `473b1c4a…` | `d0acc0c1…` | 957653162 |
|
||||
| 1 | `artifacts/partitions/xiiotid__alpha0.75__seed1.json` | `4a50ba21…` | `a0ec9e9c…` | `880a9f82…` | 762050403 |
|
||||
| 2 | `artifacts/partitions/xiiotid__alpha0.75__seed2.json` | `922b7bb1…` | `00345255…` | `8e0db0be…` | 843543396 |
|
||||
|
||||
Pairing proof: round-0 snapshot byte-identical across the five betas **and**
|
||||
`original_protean` within each seed — seed 0 `cd821beb…`, seed 1 `59d2d2bc…`, seed 2
|
||||
`47befeff…`. `train_support_Nij.csv`, `characterization.csv`, `rare_unseen.csv` identical
|
||||
across each seed's runs. `manifest_reload_ok = true`, `smoke = false` everywhere.
|
||||
Pairing proof: round-0 snapshot byte-identical across the five betas **and** `original_protean`
|
||||
within each seed — seed 0 `8c477df6…`, seed 1 `41f0187c…`, seed 2 `be2ad5fb…`.
|
||||
`train_support_Nij.csv`, `characterization.csv`, `rare_unseen.csv` identical across each seed's
|
||||
runs. `manifest_reload_ok = true`, `smoke = false` everywhere.
|
||||
|
||||
## 5. Validation results (USED FOR SELECTION) and pooled selection
|
||||
|
||||
Primary metric: validation per-client-mean rare-class macro-F1. All 10 clients eligible in
|
||||
every seed. Full tables: `artifacts/analysis/xiiotid__alpha0.25__multiseed__validation_per_seed.csv`.
|
||||
every seed. Full tables:
|
||||
`artifacts/analysis/xiiotid__alpha0.75__multiseed__validation_per_seed.csv`.
|
||||
|
||||
Per-seed validation per-client-mean rare-class macro-F1:
|
||||
|
||||
| beta | seed 0 | seed 1 | seed 2 |
|
||||
|---|---|---|---|
|
||||
| 0.00 | 0.616380 | 0.492425 | 0.666307 |
|
||||
| 0.25 | 0.609913 | 0.514237 | 0.641922 |
|
||||
| 0.50 | 0.595247 | 0.537040 | 0.625267 |
|
||||
| 0.75 | 0.654033 | 0.535672 | 0.548685 |
|
||||
| 1.00 | 0.578385 | 0.530942 | 0.486970 |
|
||||
| 0.00 | 0.496803 | 0.408276 | 0.510038 |
|
||||
| 0.25 | 0.496892 | 0.421386 | 0.504827 |
|
||||
| 0.50 | 0.504388 | 0.422919 | 0.502942 |
|
||||
| 0.75 | 0.486868 | 0.421053 | 0.509702 |
|
||||
| 1.00 | 0.479146 | 0.419534 | 0.507136 |
|
||||
|
||||
Pooled across seeds (`...__validation_pooled.csv`):
|
||||
|
||||
| beta | pooled mean | std (sample) | min | max | selected |
|
||||
|---|---|---|---|---|---|
|
||||
| **0.00** | **0.591704** | 0.089529 | 0.492425 | 0.666307 | **yes** |
|
||||
| 0.25 | 0.588691 | 0.066435 | 0.514237 | 0.641922 | |
|
||||
| 0.50 | 0.585851 | 0.044858 | 0.537040 | 0.625267 | |
|
||||
| 0.75 | 0.579463 | 0.064906 | 0.535672 | 0.654033 | |
|
||||
| 1.00 | 0.532099 | 0.045718 | 0.486970 | 0.578385 | |
|
||||
| 0.00 | 0.471706 | 0.055329 | 0.408276 | 0.510038 | |
|
||||
| 0.25 | 0.474368 | 0.046055 | 0.421386 | 0.504827 | |
|
||||
| **0.50** | **0.476749** | 0.046624 | 0.422919 | 0.504388 | **yes** |
|
||||
| 0.75 | 0.472541 | 0.046028 | 0.421053 | 0.509702 | |
|
||||
| 1.00 | 0.468605 | 0.044742 | 0.419534 | 0.507136 | |
|
||||
|
||||
- **PRIMARY selected beta (`beta_star_alpha025`) = 0.00**, max pooled validation
|
||||
- **PRIMARY selected beta (`beta_star_alpha075`) = 0.50**, max pooled validation
|
||||
per-client-mean rare-class macro-F1; **no tie-break used**; selection is validation-only.
|
||||
- **SECONDARY per-seed diagnostics only:** seed 0 → 0.75, seed 1 → 0.50, seed 2 → 0.00.
|
||||
- **SECONDARY per-seed diagnostics only:** seed 0 → 0.50, seed 1 → 0.50, seed 2 → 0.00.
|
||||
|
||||
## 6. Final test evaluation of the pooled-selected beta
|
||||
|
||||
`beta_star = 0.00` was fixed from pooled validation before test was read.
|
||||
`beta_star = 0.50` was fixed from pooled validation before test was read.
|
||||
|
||||
| metric (test) | seed 0 | seed 1 | seed 2 | mean ± std (sample) |
|
||||
|---|---|---|---|---|
|
||||
| rare-class macro-F1 | 0.641362 | 0.580555 | 0.674489 | 0.632136 ± 0.047642 |
|
||||
| rare-class recall | 0.830701 | 0.825699 | 0.807370 | 0.821257 ± 0.012283 |
|
||||
| macro-F1 | 0.674558 | 0.665039 | 0.704433 | 0.681343 ± 0.020555 |
|
||||
| accuracy | 0.874551 | 0.863490 | 0.884002 | 0.874015 ± 0.010267 |
|
||||
| weighted-F1 | 0.906156 | 0.899864 | 0.914627 | 0.906882 ± 0.007408 |
|
||||
| rare-class macro-F1 | 0.511889 | 0.624144 | 0.679704 | 0.605246 ± 0.085489 |
|
||||
| rare-class recall | 0.803887 | 0.876726 | 0.865681 | 0.848765 ± 0.039256 |
|
||||
| macro-F1 | 0.741977 | 0.761752 | 0.769179 | 0.757636 ± 0.014060 |
|
||||
| accuracy | 0.914365 | 0.932611 | 0.937352 | 0.928110 ± 0.012137 |
|
||||
| weighted-F1 | 0.935566 | 0.948344 | 0.951740 | 0.945216 ± 0.008528 |
|
||||
|
||||
`original_protean` for the same seeds/condition:
|
||||
|
||||
| metric (test) | seed 0 | seed 1 | seed 2 | mean ± std (sample) |
|
||||
|---|---|---|---|---|
|
||||
| rare-class macro-F1 | 0.639810 | 0.582522 | 0.676039 | 0.632790 ± 0.047152 |
|
||||
| rare-class recall | 0.829601 | 0.826700 | 0.809595 | 0.821965 ± 0.010811 |
|
||||
| macro-F1 | 0.673103 | 0.666981 | 0.705969 | 0.682018 ± 0.020967 |
|
||||
| accuracy | 0.873722 | 0.867341 | 0.885231 | 0.875431 ± 0.009067 |
|
||||
| weighted-F1 | 0.905466 | 0.902075 | 0.915416 | 0.907652 ± 0.006934 |
|
||||
| rare-class macro-F1 | 0.521540 | 0.614061 | 0.676068 | 0.603890 ± 0.077764 |
|
||||
| rare-class recall | 0.816440 | 0.883238 | 0.869835 | 0.856504 ± 0.035338 |
|
||||
| macro-F1 | 0.742471 | 0.747395 | 0.765680 | 0.751849 ± 0.012228 |
|
||||
| accuracy | 0.913254 | 0.913898 | 0.934576 | 0.920576 ± 0.012129 |
|
||||
| weighted-F1 | 0.932563 | 0.935937 | 0.948908 | 0.939136 ± 0.008629 |
|
||||
|
||||
Descriptive difference for test rare-class macro-F1 (`beta_star` − `original_protean`) is
|
||||
+0.001552 / −0.001967 / −0.001550 (mean −0.000655) — i.e. essentially identical, as expected
|
||||
because `beta = 0` is mathematically the equal mean over `S_j`. Test is descriptive only; no
|
||||
superiority or generalisation is claimed.
|
||||
−0.009651 / +0.010083 / +0.003636 (mean +0.001356). Test is descriptive only; no superiority
|
||||
or generalisation claimed.
|
||||
|
||||
## 7. `beta = 0` equivalence result (all three seeds)
|
||||
|
||||
For seeds 0, 1, 2, `support_weighted beta=0` vs frozen `original_protean`:
|
||||
|
||||
- Same manifest/split/hashes: **yes**.
|
||||
- Round-0 snapshot byte-identical: **yes** (`cd821beb…`, `59d2d2bc…`, `47befeff…`).
|
||||
- Round-0 snapshot byte-identical: **yes** (`8c477df6…`, `41f0187c…`, `be2ad5fb…`).
|
||||
- `train_support_Nij.csv`, `characterization.csv`, `rare_unseen.csv`: **identical**.
|
||||
- Independent aggregation (`ΣC/n` vs `(1/n)ΣC`): ≤ 4.4e-16 (1 ULP ordering).
|
||||
- Test/history/per-client/per-class: **differ slightly** (history rare-macro-F1 max diff
|
||||
3.6e-3–6.6e-3; test metric max diff 1.6e-3–3.9e-3).
|
||||
- Independent aggregation (`ΣC/n` vs `(1/n)ΣC`): 4.4e-16 / 4.4e-16 / 2.2e-16.
|
||||
- History rare-macro-F1 max diff (rounds ≥ 1): 1.10e-2 / 8.12e-3 / 3.64e-3; test metric max
|
||||
diff 4.33e-3 / 1.14e-3 / 0.85e-3.
|
||||
- Classification: **B — mathematically equivalent + floating-point numerical divergence; no
|
||||
semantic discrepancy** in any seed. Machine-readable:
|
||||
`artifacts/analysis/xiiotid__alpha0.25__multiseed__beta0_equivalence.csv`.
|
||||
`artifacts/analysis/xiiotid__alpha0.75__multiseed__beta0_equivalence.csv`.
|
||||
|
||||
Conditional on the shared `S_j` reproduction assumption; not proof `beta=0` reproduces
|
||||
original PROTEAN.
|
||||
Conditional on the shared `S_j` reproduction assumption; not proof `beta=0` reproduces original
|
||||
PROTEAN.
|
||||
|
||||
## 8. Partition characterization (realized)
|
||||
|
||||
`|S_j| < M` class-condition cells and missing client-class cells (training split):
|
||||
`|S_j| < M` class-condition cells, missing client-class cells, and client-size ratios
|
||||
(training split):
|
||||
|
||||
| condition | `|S_j| < M` cells | missing client-class cells | client-size max/min (seeds) |
|
||||
|---|---|---|---|
|
||||
| alpha=0.25 | **19 / 27** | **38** | 15.6, 20.8, 7.8 |
|
||||
| alpha=0.50 | 7 / 27 | 9 | 5.1, 7.2, 9.9 |
|
||||
| condition | `|S_j| < M` cells | missing client-class cells | client-size ratio (seeds) | union unseen | mean class CV |
|
||||
|---|---|---|---|---|---|
|
||||
| alpha=0.25 | **19 / 27** | **38** | 15.6, 20.8, 7.8 | 6/6/5 | 1.442 |
|
||||
| alpha=0.50 | 7 / 27 | 9 | 5.1, 7.2, 9.9 | 3/3/1 | 1.183 |
|
||||
| alpha=0.75 | **3 / 27** | **4** | 4.15, 5.07, 4.78 | 2/1/0 | 0.881 |
|
||||
|
||||
Union unseen classes per seed: alpha=0.25 = 6/6/5 (max 4 on a client); alpha=0.50 = 3/3/1
|
||||
(max 2). Union rare classes per seed: alpha=0.25 = 8/7/8; alpha=0.50 = 6/7/7. All clients have
|
||||
exactly two rare classes at both alphas. Full per-class `N_ij`, CV and max/min in
|
||||
`docs/research/ALPHA025_BETA_VALIDATION.md` §B. The lower alpha does **not** uniformly increase
|
||||
every realized statistic (e.g. alpha=0.25 seed 2 client-size ratio 7.8 < alpha=0.50 seed 2's
|
||||
9.9), so interpretation uses the realized partitions, not alpha alone.
|
||||
Union rare classes per seed: alpha=0.75 = 4/5/6; all clients have exactly two rare classes.
|
||||
Full per-class `N_ij`, CV and max/min in `docs/research/ALPHA075_BETA_VALIDATION.md` §C and
|
||||
`artifacts/analysis/xiiotid__cross_alpha__partition_heterogeneity_*.csv`. Heterogeneity
|
||||
decreases with alpha overall but is **not uniformly monotone per seed** (alpha=0.75 seed 0
|
||||
ratio 4.15 < seed 2's 4.78; alpha=0.50 seed 2 ratio 9.9 > alpha=0.25 seed 2's 7.8), so
|
||||
interpretation uses realized partitions, not alpha alone.
|
||||
|
||||
## 9. Direct prototype-effect findings (fixed round-0 snapshots, no retraining)
|
||||
|
||||
`||Cbar_j(1) - Cbar_j(0)||`, cross-seed mean (std), alpha=0.25 vs alpha=0.50:
|
||||
`||Cbar_j(1) - Cbar_j(0)||`, cross-seed mean, alpha=0.25 vs 0.50 vs 0.75 (mean across classes
|
||||
3.422 / 2.099 / **1.305**):
|
||||
|
||||
| class | a25 mean (std) | a50 mean (std) |
|
||||
|---|---|---|
|
||||
| Exfiltration | 4.316 (0.898) | 2.020 (0.502) |
|
||||
| Tampering | 4.248 (0.241) | 2.354 (1.165) |
|
||||
| C&C | 4.020 (0.290) | 1.694 (0.505) |
|
||||
| Lateral_movement | 3.726 (1.383) | 2.724 (1.035) |
|
||||
| Exploitation | 3.464 (1.113) | 2.344 (0.412) |
|
||||
| Reconnaissance | 3.339 (1.107) | 1.002 (0.261) |
|
||||
| Weaponization | 3.124 (0.585) | 2.561 (1.228) |
|
||||
| RDOS | 2.566 (1.219) | 2.631 (1.165) |
|
||||
| Normal | 1.997 (0.533) | 1.557 (0.548) |
|
||||
| class | a25 | a50 | a75 |
|
||||
|---|---|---|---|
|
||||
| Tampering | 4.248 | 2.354 | 1.934 |
|
||||
| Exfiltration | 4.316 | 2.020 | 1.448 |
|
||||
| Exploitation | 3.464 | 2.344 | 1.539 |
|
||||
| Lateral_movement | 3.726 | 2.724 | 1.369 |
|
||||
| C&C | 4.020 | 1.694 | 1.284 |
|
||||
| Weaponization | 3.124 | 2.561 | 1.472 |
|
||||
| Reconnaissance | 3.339 | 1.002 | 0.983 |
|
||||
| Normal | 1.997 | 1.557 | 0.903 |
|
||||
| RDOS | 2.566 | 2.631 | 0.814 |
|
||||
|
||||
Mean displacement across classes is larger at alpha=0.25 (3.42) than alpha=0.50 (2.10), because
|
||||
support is more imbalanced and more classes are missing contributors. Displacement is a
|
||||
direct-aggregation measure only, not a detection result. Outputs:
|
||||
`artifacts/analysis/xiiotid__alpha0.25__multiseed__prototype_effect_pooled.csv` and per-seed
|
||||
Displacement tracks realized support imbalance and is a direct-aggregation measure only, not a
|
||||
detection result. Outputs:
|
||||
`artifacts/analysis/xiiotid__alpha0.75__multiseed__prototype_effect_pooled.csv` and per-seed
|
||||
`...__seed{0,1,2}__support_weighted__beta0__prototype_snapshot__prototype_effect.csv`.
|
||||
|
||||
## 10. Client-level findings (validation, vs beta = 0)
|
||||
|
||||
Detail: `...__multiseed__client_validation_detail.csv`; summary:
|
||||
`...__client_validation_summary.csv`.
|
||||
Detail: `...__client_validation_detail.csv`; summary: `...__client_validation_summary.csv`; and
|
||||
`artifacts/analysis/xiiotid__cross_alpha__cross_alpha_client_summary.csv`.
|
||||
|
||||
- At alpha=0.25 the higher-beta response is **seed-dependent and often negative**:
|
||||
improve/degrade/unchanged at beta=0.75 = 5/4/1 (seed 0, mean Δ +0.038), 5/4/1 (seed 1,
|
||||
+0.043), 3/5/2 (seed 2, −0.118). At beta=1.00 seed 2 degrades 6/10 clients with a worst
|
||||
client Δ = −0.678, while seed 1 still gains on average.
|
||||
- This **contrasts with alpha=0.50**, where beta=0.75 improved the majority of clients in every
|
||||
seed. Client ids are per-seed realisations and are not one population; the analysis is
|
||||
descriptive and non-causal, and `N_ij` vs ΔF1 remains non-monotonic.
|
||||
- At alpha=0.75, the response is smaller and seed-dependent. At the selected `beta=0.50`:
|
||||
6/4/0 (seed 0, mean Δ +0.008), 9/0/1 (seed 1, +0.015), 6/4/0 (seed 2, −0.007; worst client
|
||||
−0.152).
|
||||
- At a common `beta=0.75`: alpha=0.25 = 5/4/1, 5/4/1, 3/5/2 (often negative); alpha=0.50 =
|
||||
7/3/0, 8/1/1, 8/1/1 (majority improve); alpha=0.75 = 3/7/0, 9/0/1, 5/5/0.
|
||||
- `N_ij` vs ΔF1 remains non-monotonic at every alpha. Client ids are per-seed realisations and
|
||||
are not pooled.
|
||||
|
||||
## 11. Comparison with alpha=0.50 (RQ3)
|
||||
## 11. Three-alpha comparison (RQ3)
|
||||
|
||||
| | alpha=0.50 | alpha=0.25 |
|
||||
|---|---|---|
|
||||
| pooled-selected beta | 0.75 | **0.00** |
|
||||
| pooled validation curve | rises to 0.75 | monotone decreasing |
|
||||
| pooled mean range | 0.544–0.579 | 0.532–0.592 |
|
||||
| pooled std range | 0.075–0.100 | 0.045–0.090 |
|
||||
| `|S_j| < M` cells | 7/27 | 19/27 |
|
||||
| mean `||Cbar(1)−Cbar(0)||` | 2.10 | 3.42 |
|
||||
| | alpha=0.25 | alpha=0.50 | alpha=0.75 |
|
||||
|---|---|---|---|
|
||||
| pooled-selected beta | **0.00** | **0.75** | **0.50** |
|
||||
| pooled validation curve | monotone decreasing | rises to peak at 0.75 | peaks at 0.50 |
|
||||
| pooled mean range (spread) | 0.532–0.592 (0.060) | 0.544–0.579 (0.035) | 0.469–0.477 (0.008) |
|
||||
| pooled std range | 0.045–0.090 | 0.075–0.100 | 0.045–0.055 |
|
||||
| `|S_j| < M` cells | 19/27 | 7/27 | 3/27 |
|
||||
| mean `||Cbar(1)−Cbar(0)||` | 3.422 | 2.099 | 1.305 |
|
||||
|
||||
The selection **changes** with non-IID severity. This is documented as a descriptive
|
||||
association accompanied by the realized partition characteristics; **no causal claim is made
|
||||
that alpha by itself caused the difference**. The effect is small relative to between-seed
|
||||
variance at both settings.
|
||||
The pooled-selected beta **changes** with the non-IID condition (0.00 → 0.75 → 0.50) but is
|
||||
**not monotone** in alpha. This is documented as a descriptive association accompanied by the
|
||||
realized partition characteristics; **no causal claim** is made. With only three alpha levels,
|
||||
three project-defined seeds, one dataset and no inferential trend test, monotonicity is not
|
||||
claimed.
|
||||
|
||||
> **Audited label (do not confuse).** Condition-level **pooled** selections are alpha=0.50 →
|
||||
> **0.75** and alpha=0.25 → **0.00**. The value **0.50** is only the Session-5 **seed-0
|
||||
> single-condition** choice and the Session-6 alpha=0.50 **per-seed diagnostic** for seed 0;
|
||||
> it is not the alpha=0.50 pooled selection. Any "0.50 → 0.00" phrasing for condition-level
|
||||
> pooled selection is wrong. Verified in `docs/research/SESSION7_AUDIT.md` §M.
|
||||
> **Audited label (do not confuse).** Condition-level **pooled** selections are alpha=0.25 →
|
||||
> **0.00**, alpha=0.50 → **0.75**, alpha=0.75 → **0.50**. The value **0.50** is *not* the
|
||||
> alpha=0.50 pooled selection: it is only the Session-5 **seed-0 single-condition** choice, the
|
||||
> Session-6 alpha=0.50 **per-seed diagnostic** for seed 0, and now the alpha=0.75 pooled
|
||||
> selection. See `docs/research/SESSION7_AUDIT.md` §M and `SESSION8_AUDIT.md` §M.
|
||||
|
||||
## 12. Runtime / resources
|
||||
|
||||
CPU only, no GPU, no swap, exit 0 on all 18 runs. Per-run wall-clock 39:49–42:12; CPU
|
||||
741–746 %; peak RSS 8.38 GiB (seed 0), 10.80 GiB (seed 1), 7.51 GiB (seed 2). New compute:
|
||||
18 runs, ≈ 43,799 s ≈ **12.17 h** wall-clock, sequential (8 cores). Machine-readable:
|
||||
`artifacts/analysis/xiiotid__alpha0.25__multiseed__runtime.csv`.
|
||||
CPU only, no GPU, no swap, exit 0 on all 18 runs. Per-run wall-clock 40:00–49:02 (two runs
|
||||
slower under transient host contention); CPU 714–746 %; peak RSS 6.49 GiB (seed 0), 6.91 GiB
|
||||
(seed 1), 7.20 GiB (seed 2). New compute: 18 runs, 44,371 s ≈ **12.33 h** wall-clock,
|
||||
sequential (8 cores). Machine-readable:
|
||||
`artifacts/analysis/xiiotid__alpha0.75__multiseed__runtime.csv`.
|
||||
|
||||
## 13. Methodological decisions / assumptions
|
||||
|
||||
1. **`S_j` participant/denominator rule** (`S_j = {i | N_ij > 0 and valid C_ij}`, equal
|
||||
weights in the baseline) is a **REPRODUCTION ASSUMPTION**; material in 19/27
|
||||
class-condition cells at alpha=0.25 (7/27 at alpha=0.50). Carry this caveat in all reporting.
|
||||
1. **`S_j` participant/denominator rule** (`S_j = {i | N_ij > 0 and valid C_ij}`, equal weights
|
||||
in the baseline) is a **REPRODUCTION ASSUMPTION**; material in 19/27 class-condition cells at
|
||||
alpha=0.25, 7/27 at alpha=0.50, 3/27 at alpha=0.75. Carry this caveat in all reporting.
|
||||
2. `N_ij` is class-specific sample support, not prototype quality.
|
||||
3. Beta is one value for all classes/clients; candidates frozen at `{0,.25,.5,.75,1}`.
|
||||
4. **PRIMARY selection = pooled validation across clients and seeds**; per-seed selection is
|
||||
secondary stability diagnostics; test used only after the pooled beta is fixed.
|
||||
5. The `scripts/analyze_multiseed_beta.py` already supported `--alpha` (default 0.5) and
|
||||
already includes alpha in output names; **no code change was needed**. alpha=0.50 outputs
|
||||
were re-run and are byte-identical to the Session-6 artifacts (reproducibility verified).
|
||||
5. Three new read-only analysis scripts were added this session (no training/aggregation code
|
||||
changed): `scripts/analyze_partition_heterogeneity.py`,
|
||||
`scripts/verify_beta0_equivalence.py`, `scripts/analyze_cross_alpha.py`.
|
||||
6. `lambda=1.0`, Adam, lr 1e-3, batch 256 remain PROJECT DECISIONS. No `equal_available` mode.
|
||||
|
||||
## 14. Unresolved questions / blockers
|
||||
|
||||
1. `S_j` reproduction ambiguity — unresolved; no official PROTEAN code exists.
|
||||
2. **Pooled beta selection remains statistically weak at both alphas (descriptive only):**
|
||||
the across-seed sample std (0.045–0.090) is comparable to, or larger than, the total
|
||||
between-beta pooled-mean spread (0.035 at alpha=0.50, 0.060 at alpha=0.25). No inferential
|
||||
test was performed, so this is a descriptive comparison, not evidence of insignificance.
|
||||
3. `beta = 0` is not bitwise identical to `original_protean`; documentation decision on how to
|
||||
report this remains open.
|
||||
2. **Pooled beta selection remains statistically weak at all three alphas (descriptive only):**
|
||||
the across-seed sample std is comparable to or larger than the between-beta spread. No
|
||||
inferential test was performed.
|
||||
3. `beta = 0` is not bitwise identical to `original_protean`; the documentation decision on how
|
||||
to report this remains open.
|
||||
4. Session-2 manifests still store `preprocessing_hash = null` / `config_hash = null`.
|
||||
5. Only alpha=0.25 and 0.50, X-IIoTID, three seeds measured. No 5G-NIDD beta result.
|
||||
6. The alpha=0.25 result (pooled-selected beta = 0) is **one additional condition, not yet a
|
||||
trend across alpha**. Whether any relationship between non-IID severity and the selected beta
|
||||
is monotone would require alpha=0.75 (and is still not implied by two conditions).
|
||||
5. Only alpha=0.25/0.50/0.75, X-IIoTID, three seeds measured. No 5G-NIDD beta result.
|
||||
6. The three-alpha selected-beta sequence (0.00 / 0.75 / 0.50) is **not monotone**; no trend
|
||||
claim is made and no inference has been run.
|
||||
|
||||
## 15. Git status
|
||||
|
||||
No commit or push was made. `git status --short` shows only untracked docs/analysis/run
|
||||
artifacts (`results/` is gitignored; `artifacts/analysis/` is intentionally tracked):
|
||||
artifacts and the three new scripts (`results/` is gitignored; `artifacts/analysis/` is
|
||||
intentionally tracked):
|
||||
|
||||
```
|
||||
M docs/handoff/SESSION_HANDOFF.md
|
||||
?? docs/research/ALPHA025_BETA_VALIDATION.md
|
||||
?? docs/research/SESSION7_AUDIT.md
|
||||
?? artifacts/analysis/xiiotid__alpha0.25__* (runs' snapshots, effect CSVs, multiseed tables)
|
||||
?? (pre-existing Session-5/6 untracked alpha=0.5 views, unchanged)
|
||||
?? docs/research/ALPHA075_BETA_VALIDATION.md
|
||||
?? docs/research/XIIOTID_CROSS_ALPHA_ANALYSIS.md
|
||||
?? docs/research/SESSION8_AUDIT.md
|
||||
?? scripts/analyze_cross_alpha.py
|
||||
?? scripts/analyze_partition_heterogeneity.py
|
||||
?? scripts/verify_beta0_equivalence.py
|
||||
?? artifacts/analysis/xiiotid__alpha0.75__* (runs' snapshots, effect CSVs, multiseed tables)
|
||||
?? artifacts/analysis/xiiotid__cross_alpha__* (heterogeneity, cross-alpha tables)
|
||||
?? (pre-existing Session-5/6/7 untracked alpha=0.25/0.5 views, unchanged)
|
||||
```
|
||||
|
||||
`planningawal/` and both raw datasets are unchanged (audit re-verified SHA-256:
|
||||
X-IIoTID `7b929005…`, 5G-NIDD `fa36f808…`). No model/training/aggregation source changed
|
||||
(working-tree blobs equal HEAD). `artifacts/partitions/` unmodified. No alpha=0.75 run and no
|
||||
5G-NIDD `support_weighted` run exists. `equal_available` absent.
|
||||
`HEAD = 6b97a0d38b839c737c49f41006817503d0672871`. No commit or push was made.
|
||||
No tracked source/test/config file differs from HEAD. `planningawal/` and both raw datasets are
|
||||
unchanged (audit re-verified SHA-256: X-IIoTID `7b929005…`, 5G-NIDD `fa36f808…`).
|
||||
`artifacts/partitions/` unmodified. No 5G-NIDD `support_weighted` run exists. `equal_available`
|
||||
absent. `HEAD = ff68d380e23859d21c07c8a3a7b56b1b7f06c91b`. No commit or push was made.
|
||||
|
||||
## 15b. Session 7 audit result (independent)
|
||||
## 16. Session 8 audit result
|
||||
|
||||
- Verdict: **PASS WITH MINOR CORRECTIONS** (`docs/research/SESSION7_AUDIT.md`).
|
||||
- Verdict: **PASS** (`docs/research/SESSION8_AUDIT.md`).
|
||||
- Run inventory 18/18, pairing hash-identical, manifests reproduced from raw data.
|
||||
- Validation recomputed exactly; **pooled `beta_star(alpha=0.25) = 0.00`** (validation only,
|
||||
monotone decreasing in beta). `beta_star` test and `original_protean` test means/stds exact.
|
||||
- Leakage audit: selection reads validation only; `test_used_for_selection=false` upheld.
|
||||
- Validation recomputed exactly; **pooled `beta_star(alpha=0.75) = 0.50`** (validation only).
|
||||
`beta_star` test and `original_protean` test means/stds exact.
|
||||
- Leakage audit PASS; `test_used_for_selection=false` upheld.
|
||||
- `beta=0` equivalence: class **B** for all three seeds (no semantic discrepancy).
|
||||
- Source/data integrity: PASS. pytest: **75 passed, 0 failed, 0 skipped, 0 warnings**.
|
||||
- Corrections: cross-alpha label disambiguation (documentation-only) and one wording nuance.
|
||||
No arithmetic, metric-label, std-convention, or provenance defect was found.
|
||||
- Direct-effect, client-level, rare/unseen, cross-alpha labels: PASS.
|
||||
- Source/data integrity PASS. pytest: **75 passed, 0 failed, 0 skipped, 0 warnings**.
|
||||
|
||||
## 16. Files created / modified this session
|
||||
## 17. Files created / modified this session
|
||||
|
||||
Created:
|
||||
|
||||
- `docs/research/ALPHA025_BETA_VALIDATION.md`
|
||||
- `docs/research/SESSION7_AUDIT.md` (independent post-experiment audit)
|
||||
- `artifacts/analysis/xiiotid__alpha0.25__seed{0,1,2}__*__prototype_snapshot.json`
|
||||
- `artifacts/analysis/xiiotid__alpha0.25__seed{0,1,2}__support_weighted__beta0__prototype_snapshot__{prototype_effect,prototype_weights}.csv`
|
||||
- `artifacts/analysis/xiiotid__alpha0.25__multiseed__{validation_per_seed,validation_pooled,client_validation_deltas,client_validation_detail,client_validation_summary,prototype_effect_pooled,test_descriptive,runtime,beta0_equivalence}.csv` and `...__selection_summary.json`
|
||||
- `results/xiiotid__alpha0.25__seed{0,1,2}__*` (18 run dirs, gitignored)
|
||||
- `docs/research/ALPHA075_BETA_VALIDATION.md`
|
||||
- `docs/research/XIIOTID_CROSS_ALPHA_ANALYSIS.md`
|
||||
- `docs/research/SESSION8_AUDIT.md`
|
||||
- `scripts/analyze_partition_heterogeneity.py`
|
||||
- `scripts/verify_beta0_equivalence.py`
|
||||
- `scripts/analyze_cross_alpha.py`
|
||||
- `artifacts/analysis/xiiotid__alpha0.75__*` (run snapshots, effect/weights CSVs, multiseed
|
||||
tables, `beta0_equivalence.csv`, `runtime.csv`)
|
||||
- `artifacts/analysis/xiiotid__cross_alpha__*` (partition heterogeneity per-seed/per-class/summary,
|
||||
cross-alpha beta table/displacement/client summary/summary)
|
||||
- `results/xiiotid__alpha0.75__seed{0,1,2}__*` (18 run dirs, gitignored)
|
||||
|
||||
Modified:
|
||||
|
||||
- `docs/handoff/SESSION_HANDOFF.md` (this file)
|
||||
|
||||
No source or test code was changed. `scripts/analyze_multiseed_beta.py` was re-run for
|
||||
alpha=0.50 and produced byte-identical outputs.
|
||||
No source or test code was changed.
|
||||
|
||||
## 17. Exact recommended next phase
|
||||
## 18. Exact recommended next phase
|
||||
|
||||
1. **Session 7 is audited and safe to checkpoint** (verdict PASS WITH MINOR CORRECTIONS;
|
||||
see §15b and `docs/research/SESSION7_AUDIT.md`). alpha=0.25 behaved cleanly: pairing valid,
|
||||
beta=0 class B, pooled selection clean, artifacts complete, no test leakage, runtime
|
||||
manageable (≈12 h per alpha). Before checkpointing, stage only the intended docs/analysis
|
||||
artifacts; do not commit `results/` or the raw datasets.
|
||||
2. **Next experiment:** run X-IIoTID `alpha=0.75` under the same protocol (seeds `{0,1,2}`,
|
||||
five betas + `original_protean`, sequential, reusing frozen manifests, pooled
|
||||
validation-only selection), then test evaluation, direct-effect, client-level, and
|
||||
cross-alpha comparison. This would complete the three planned non-IID severities. Do **not**
|
||||
infer a monotone alpha→beta relation from two conditions.
|
||||
3. Do **not** treat `beta = 0.00` (alpha=0.25) or `0.75` (alpha=0.50) as optima. Report each as
|
||||
"best among tested candidates under pooled validation for that condition".
|
||||
4. **Do not launch 5G-NIDD or the full grid** until alpha=0.75 is inspected.
|
||||
5. Use `.venv/bin/python`. Run one alpha at a time; measure runtime as before.
|
||||
6. Update `docs/research/ALPHA025_BETA_VALIDATION.md` (or add `ALPHA075_BETA_VALIDATION.md`),
|
||||
`EXPERIMENT_PROTOCOL.md` only if a real ambiguity appears, and this handoff. Do not commit or
|
||||
push unless asked.
|
||||
1. **Session 8 is audited and safe to checkpoint** (verdict PASS; see §16 and
|
||||
`docs/research/SESSION8_AUDIT.md`). X-IIoTID alpha=0.75 behaved cleanly. Before
|
||||
checkpointing, stage only the intended docs/scripts/analysis artifacts; do not commit
|
||||
`results/` or the raw datasets.
|
||||
2. **X-IIoTID three-alpha study is complete** (0.25, 0.50, 0.75 × seeds `{0,1,2}`), with
|
||||
audited condition-level pooled selections 0.00 / 0.75 / 0.50 and a cross-alpha report.
|
||||
3. **Next major phase: 5G-NIDD.** Follow the same protocol (the planned alphas `{0.75, 0.50,
|
||||
0.25}`, seeds `{0,1,2}`, five betas + `original_protean`, frozen manifests, pooled
|
||||
validation-only selection). Do **not** launch the full grid blindly: verify 5G-NIDD manifests
|
||||
exist and reproduce, run the same one-condition-at-a-time pacing, and measure runtime first.
|
||||
A single smoke/one-condition run before scaling is recommended.
|
||||
4. Do **not** treat any selected beta as an optimum. Report each as "best among tested
|
||||
candidates under pooled validation for that condition".
|
||||
5. Do **not** infer a monotone alpha→beta relation from three X-IIoTID conditions.
|
||||
6. Update `EXPERIMENT_PROTOCOL.md` only if a real ambiguity appears; update this handoff.
|
||||
7. Do not commit or push unless asked.
|
||||
|
||||
## 18. Important commands
|
||||
## 19. Important commands
|
||||
|
||||
```bash
|
||||
# Tests (75 expected)
|
||||
.venv/bin/python -m pytest
|
||||
|
||||
# One full paired beta run (CPU, ~40 min, ~7.5-11.3 GiB)
|
||||
.venv/bin/python scripts/run_baseline.py --dataset xiiotid --alpha 0.25 --seed 1 \
|
||||
# One full paired beta run (CPU, ~40 min, ~6.5-7.2 GiB)
|
||||
.venv/bin/python scripts/run_baseline.py --dataset xiiotid --alpha 0.75 --seed 1 \
|
||||
--clients 10 --rounds 10 --local-epochs 3 \
|
||||
--aggregation-mode support_weighted --beta 0.5
|
||||
|
||||
# Pooled multi-seed validation analysis (read-only, no retraining; --alpha already supported)
|
||||
.venv/bin/python scripts/analyze_multiseed_beta.py --dataset xiiotid --alpha 0.25 --seeds 0 1 2
|
||||
# Pooled multi-seed validation analysis (read-only, no retraining)
|
||||
.venv/bin/python scripts/analyze_multiseed_beta.py --dataset xiiotid --alpha 0.75 --seeds 0 1 2
|
||||
|
||||
# Direct prototype-effect analysis (no retraining)
|
||||
.venv/bin/python scripts/analyze_prototype_effect.py \
|
||||
--snapshot artifacts/analysis/xiiotid__alpha0.25__seed0__support_weighted__beta0__prototype_snapshot.json \
|
||||
--snapshot artifacts/analysis/xiiotid__alpha0.75__seed0__support_weighted__beta0__prototype_snapshot.json \
|
||||
--class-names "C&C,Exfiltration,Exploitation,Lateral_movement,Normal,RDOS,Reconnaissance,Tampering,Weaponization" \
|
||||
--output-dir artifacts/analysis
|
||||
|
||||
# Realized partition characterization (all alphas)
|
||||
.venv/bin/python scripts/analyze_partition_heterogeneity.py --dataset xiiotid --alphas 0.75 0.5 0.25
|
||||
|
||||
# beta=0 equivalence audit
|
||||
.venv/bin/python scripts/verify_beta0_equivalence.py --dataset xiiotid --alpha 0.75 --seeds 0 1 2
|
||||
|
||||
# Cross-alpha comparison
|
||||
.venv/bin/python scripts/analyze_cross_alpha.py --dataset xiiotid --alphas 0.25 0.5 0.75
|
||||
```
|
||||
|
||||
## 19. Recommended next-session prompt
|
||||
## 20. Recommended next-session prompt
|
||||
|
||||
```
|
||||
You are continuing the perdalam-protean research repository (Session 8).
|
||||
You are continuing the perdalam-protean research repository (Session 9).
|
||||
|
||||
FIRST, read completely:
|
||||
1. docs/handoff/SESSION_HANDOFF.md
|
||||
2. docs/research/ALPHA025_BETA_VALIDATION.md
|
||||
3. docs/research/MULTISEED_BETA_VALIDATION.md
|
||||
4. docs/research/EXPERIMENT_PROTOCOL.md
|
||||
5. docs/baseline/BASELINE_VALIDATION.md
|
||||
2. docs/research/ALPHA075_BETA_VALIDATION.md
|
||||
3. docs/research/XIIOTID_CROSS_ALPHA_ANALYSIS.md
|
||||
4. docs/research/SESSION8_AUDIT.md
|
||||
5. docs/research/EXPERIMENT_PROTOCOL.md
|
||||
6. docs/baseline/BASELINE_VALIDATION.md
|
||||
|
||||
Critical rules:
|
||||
- planningawal/ is immutable.
|
||||
@@ -383,19 +405,18 @@ Critical rules:
|
||||
- The S_j participant rule is a REPRODUCTION ASSUMPTION (material in 19/27 cells at alpha=0.25).
|
||||
- Do NOT add an executable equal_available mode.
|
||||
- Beta selection uses validation only; PRIMARY is pooled across clients and seeds.
|
||||
- Do NOT launch 5G-NIDD or the full grid.
|
||||
- Do NOT launch the full grid blindly; verify manifests and pace one condition at a time.
|
||||
|
||||
Context: Session 7 completed X-IIoTID alpha=0.25 for seeds {0,1,2} (18 runs, ~12.17 h) and was
|
||||
independently audited (PASS WITH MINOR CORRECTIONS; docs/research/SESSION7_AUDIT.md). Pooled
|
||||
validation selected beta=0.00 (pooled mean 0.591704; monotone decreasing in beta), unlike
|
||||
alpha=0.50 which selected 0.75. Per-seed diagnostics 0.75/0.50/0.00. beta=0 equivalence class B
|
||||
(no semantic discrepancy). Realized partitions more heterogeneous (19/27 |S_j|<M vs 7/27).
|
||||
Condition-level pooled labels: alpha=0.50 -> 0.75, alpha=0.25 -> 0.00 (the value 0.50 is only the
|
||||
Session-5 seed-0 choice, not a condition-level selection).
|
||||
Context: Session 8 completed X-IIoTID alpha=0.75 for seeds {0,1,2} (18 runs, ~12.33 h) and was
|
||||
independently audited (PASS; docs/research/SESSION8_AUDIT.md). Pooled validation selected
|
||||
beta=0.50. Three-alpha X-IIoTID pooled selections: alpha=0.25 -> 0.00, alpha=0.50 -> 0.75,
|
||||
alpha=0.75 -> 0.50 (NOT monotone). beta=0 equivalence class B. Realized heterogeneity: 19/27,
|
||||
7/27, 3/27 cells |S_j|<M; mean displacement 3.42 / 2.10 / 1.31.
|
||||
|
||||
Task: run X-IIoTID alpha=0.75 for seeds {0,1,2} across the five frozen betas plus
|
||||
original_protean, sequential, reusing frozen manifests, pooled validation-only selection, then
|
||||
test evaluation, direct-effect, client-level, and cross-alpha comparison. Produce
|
||||
docs/research/ALPHA075_BETA_VALIDATION.md and update the handoff. Use .venv/bin/python. Do not
|
||||
commit or push unless asked.
|
||||
Task: X-IIoTID three-alpha study is complete. Recommended next phase is 5G-NIDD under the same
|
||||
frozen protocol (alphas {0.75, 0.50, 0.25}, seeds {0,1,2}, five betas + original_protean,
|
||||
frozen manifests, pooled validation-only selection). Before scaling, verify 5G-NIDD manifests
|
||||
exist and reproduce, run one paired condition, inspect it, then proceed. Produce a 5G-NIDD beta
|
||||
validation report and a cross-dataset comparison, update the handoff. Use .venv/bin/python. Do
|
||||
not commit or push unless asked.
|
||||
```
|
||||
@@ -0,0 +1,422 @@
|
||||
# Alpha-0.75 Beta Validation (Session 8)
|
||||
|
||||
Status: **three-seed paired protocol completed for the mildest non-IID condition**
|
||||
(X-IIoTID `alpha = 0.75`, seeds `{0,1,2}`) with pooled-across-seed validation-only beta
|
||||
selection, followed by a single final test evaluation of the pooled-selected beta. This is a
|
||||
**paired characterisation of the third and final non-IID severity** planned for X-IIoTID. It
|
||||
is not a sweep, not a hyper-parameter search over seeds, and not evidence of a global optimum.
|
||||
|
||||
Companion documents:
|
||||
|
||||
- `docs/research/EXPERIMENT_PROTOCOL.md` — frozen protocol and selection hierarchy.
|
||||
- `docs/research/XIIOTID_CROSS_ALPHA_ANALYSIS.md` — three-condition (0.25/0.50/0.75) comparison.
|
||||
- `docs/research/MULTISEED_BETA_VALIDATION.md` — Session-6 alpha=0.50 condition.
|
||||
- `docs/research/ALPHA025_BETA_VALIDATION.md` — Session-7 alpha=0.25 condition.
|
||||
- `docs/research/BETA_AGGREGATION_IMPLEMENTATION.md` — beta mode implementation.
|
||||
- `docs/baseline/BASELINE_VALIDATION.md` — frozen baseline evidence.
|
||||
- `docs/handoff/SESSION_HANDOFF.md` — continuation point.
|
||||
|
||||
---
|
||||
|
||||
## A. Scope
|
||||
|
||||
| Field | Value |
|
||||
|---|---|
|
||||
| dataset | `xiiotid` (X-IIoTID) |
|
||||
| alpha | 0.75 |
|
||||
| seeds | 0, 1, 2 |
|
||||
| aggregation | `original_protean` (per seed) + `support_weighted` for `beta ∈ {0, 0.25, 0.5, 0.75, 1}` |
|
||||
| runs | 18: 15 `support_weighted` + 3 `original_protean`, all new this session |
|
||||
| compute | sequential on CPU, one run at a time, ≈ 12.33 h wall-clock total |
|
||||
|
||||
No other alpha, dataset, seed, mode or beta was run. `equal_available` was not added.
|
||||
5G-NIDD was deliberately **not** run.
|
||||
|
||||
---
|
||||
|
||||
## B. Frozen protocol
|
||||
|
||||
Identical to `EXPERIMENT_PROTOCOL.md` §14 and to Sessions 6–7: 10 clients, 10 rounds, 3 local
|
||||
epochs, batch 256, Adam `lr=1e-3`, `mu=0.1`, `lambda=1.0`; unchanged architecture,
|
||||
preprocessing, train/validation/test split recipe, partition recipe, loss terms and inference.
|
||||
All 18 runs were performed this session with `scripts/run_baseline.py` at HEAD `ff68d380`
|
||||
(no training/aggregation source changed).
|
||||
|
||||
### B.1 Manifest identity (reused, never regenerated)
|
||||
|
||||
Train/validation/test sizes are 569,909 / 81,414 / 162,831 for every seed (10 clients, 9
|
||||
classes, `Normal` benign).
|
||||
|
||||
| seed | manifest | content hash | partition hash | split hash | rng seed |
|
||||
|---|---|---|---|---|---|
|
||||
| 0 | `artifacts/partitions/xiiotid__alpha0.75__seed0.json` | `759f7e50…` | `473b1c4a…` | `d0acc0c1…` | 957653162 |
|
||||
| 1 | `artifacts/partitions/xiiotid__alpha0.75__seed1.json` | `4a50ba21…` | `a0ec9e9c…` | `880a9f82…` | 762050403 |
|
||||
| 2 | `artifacts/partitions/xiiotid__alpha0.75__seed2.json` | `922b7bb1…` | `00345255…` | `8e0db0be…` | 843543396 |
|
||||
|
||||
The split hash is identical to the corresponding seeds at alpha=0.25/0.50 (splits are
|
||||
per-dataset-seed, not per-alpha); the partition hash differs because the Dirichlet partition
|
||||
differs.
|
||||
|
||||
### B.2 Build-level pairing
|
||||
|
||||
Within each seed all six runs share one manifest content hash and a byte-identical round-0
|
||||
snapshot:
|
||||
|
||||
| seed | manifest content hash | round-0 snapshot SHA-256 (all 6 runs) |
|
||||
|---|---|---|
|
||||
| 0 | `759f7e504a7d442101238726334d121a746ea4a8ff366428c1c174e47f358723` | `8c477df6b3af645bf2db1c8005d86ea6258b283370ff3ef3e6e88d6f40095564` |
|
||||
| 1 | `4a50ba219de20af14f6ad73976111659fba2d5b25cd5eeb1a2f21b76de0d9303` | `41f0187c4f0a8e3db0a8ab7eff0aa50a8f3e4a64ded2448228bd133ea017869d` |
|
||||
| 2 | `922b7bb15169302be7dd4d4eb1644d077537872e1e91fe59b7525b7e3343cc1c` | `be2ad5fb5fcf87c49b2826936c8d5dae6cdc4ab25fe2677081acec32f8116648` |
|
||||
|
||||
`train_support_Nij.csv`, `characterization.csv` and `rare_unseen.csv` are byte-identical across
|
||||
the six runs of each seed; `manifest_reload_ok = true` and `smoke = false` everywhere. Pairing
|
||||
is established from content hashes, not filenames.
|
||||
|
||||
### B.3 Selection rule (unchanged)
|
||||
|
||||
- **PRIMARY:** pooled-across-seed validation per-client-mean rare-class macro-F1 (average each
|
||||
seed's per-client mean over seeds `{0,1,2}`), selected with validation only.
|
||||
- **SECONDARY (diagnostic):** per-seed validation selection, stability only.
|
||||
- **TEST:** read only after the pooled beta is fixed.
|
||||
|
||||
---
|
||||
|
||||
## C. Partition characterization (realized, before interpretation)
|
||||
|
||||
`M = 10` clients; `|S_j| < M` means fewer than 10 clients contribute a class prototype. All
|
||||
statistics are from the training split `N_ij`.
|
||||
|
||||
### Per-seed summary
|
||||
|
||||
| seed | `|S_j| < M` cells | missing client-class cells | client-size min/max (ratio) | union rare | union unseen | max unseen on a client |
|
||||
|---|---|---|---|---|---|---|
|
||||
| 0 | 2 / 9 | 3 | 24,236 / 100,573 (4.15) | 4 | 2 | 1 |
|
||||
| 1 | 1 / 9 | 1 | 21,623 / 109,690 (5.07) | 5 | 1 | 1 |
|
||||
| 2 | 0 / 9 | 0 | 24,224 / 115,896 (4.78) | 6 | 0 | 0 |
|
||||
| **total / mean** | **3 / 27** | **4** | ratio mean **4.67** | 4/5/6 | 2/1/0 | 1 |
|
||||
|
||||
Every client has exactly two rare classes in every seed. Union rare classes per seed:
|
||||
seed 0 = `C&C, Exfiltration, Exploitation, Tampering`; seed 1 adds `RDOS`;
|
||||
seed 2 adds `Lateral_movement` and `Weaponization`. Unseen unions: seed 0 =
|
||||
`{C&C, Exploitation}`, seed 1 = `{C&C}`, seed 2 = `{}`.
|
||||
|
||||
### Per-class `N_ij` inequality (training split)
|
||||
|
||||
`CV` is the population coefficient of variation of the positive supports within a class;
|
||||
`max/min` is over contributing clients only.
|
||||
|
||||
**Seed 0**
|
||||
|
||||
| class | total | #clients | min+ | max | mean+ | CV | max/min |
|
||||
|---|---|---|---|---|---|---|---|
|
||||
| C&C | 2,004 | 8 | 5 | 760 | 250.5 | 0.888 | 152.0 |
|
||||
| Exfiltration | 15,494 | 10 | 27 | 4,392 | 1,549.4 | 0.846 | 162.7 |
|
||||
| Exploitation | 793 | 9 | 1 | 240 | 88.1 | 0.875 | 240.0 |
|
||||
| Lateral_movement | 22,117 | 10 | 190 | 5,435 | 2,211.7 | 0.888 | 28.6 |
|
||||
| Normal | 292,777 | 10 | 1,151 | 92,460 | 29,277.7 | 0.912 | 80.3 |
|
||||
| RDOS | 98,883 | 10 | 347 | 22,821 | 9,888.3 | 0.770 | 65.8 |
|
||||
| Reconnaissance | 89,161 | 10 | 458 | 23,824 | 8,916.1 | 0.982 | 52.0 |
|
||||
| Tampering | 3,586 | 10 | 31 | 1,227 | 358.6 | 1.176 | 39.6 |
|
||||
| Weaponization | 45,094 | 10 | 285 | 12,915 | 4,509.4 | 0.906 | 45.3 |
|
||||
|
||||
**Seed 1**
|
||||
|
||||
| class | total | #clients | min+ | max | mean+ | CV | max/min |
|
||||
|---|---|---|---|---|---|---|---|
|
||||
| C&C | 2,004 | 9 | 87 | 538 | 222.7 | 0.612 | 6.2 |
|
||||
| Exfiltration | 15,494 | 10 | 239 | 3,749 | 1,549.4 | 0.879 | 15.7 |
|
||||
| Exploitation | 793 | 10 | 4 | 246 | 79.3 | 0.997 | 61.5 |
|
||||
| Lateral_movement | 22,117 | 10 | 556 | 4,082 | 2,211.7 | 0.596 | 7.3 |
|
||||
| Normal | 292,777 | 10 | 4,311 | 73,956 | 29,277.7 | 0.818 | 17.2 |
|
||||
| RDOS | 98,883 | 10 | 268 | 34,051 | 9,888.3 | 0.936 | 127.1 |
|
||||
| Reconnaissance | 89,161 | 10 | 520 | 22,127 | 8,916.1 | 0.781 | 42.6 |
|
||||
| Tampering | 3,586 | 10 | 25 | 1,004 | 358.6 | 0.857 | 40.2 |
|
||||
| Weaponization | 45,094 | 10 | 269 | 10,726 | 4,509.4 | 0.796 | 39.9 |
|
||||
|
||||
**Seed 2**
|
||||
|
||||
| class | total | #clients | min+ | max | mean+ | CV | max/min |
|
||||
|---|---|---|---|---|---|---|---|
|
||||
| C&C | 2,004 | 10 | 1 | 546 | 200.4 | 0.917 | 546.0 |
|
||||
| Exfiltration | 15,494 | 10 | 9 | 3,572 | 1,549.4 | 0.860 | 396.9 |
|
||||
| Exploitation | 793 | 10 | 11 | 382 | 79.3 | 1.322 | 34.7 |
|
||||
| Lateral_movement | 22,117 | 10 | 3 | 5,709 | 2,211.7 | 0.879 | 1,903.0 |
|
||||
| Normal | 292,777 | 10 | 1,930 | 64,353 | 29,277.7 | 0.791 | 33.3 |
|
||||
| RDOS | 98,883 | 10 | 636 | 18,655 | 9,888.3 | 0.564 | 29.3 |
|
||||
| Reconnaissance | 89,161 | 10 | 1,528 | 21,418 | 8,916.1 | 0.692 | 14.0 |
|
||||
| Tampering | 3,586 | 10 | 1 | 1,321 | 358.6 | 1.112 | 1,321.0 |
|
||||
| Weaponization | 45,094 | 10 | 169 | 17,328 | 4,509.4 | 1.126 | 102.5 |
|
||||
|
||||
Machine-readable: `artifacts/analysis/xiiotid__cross_alpha__partition_heterogeneity_per_class.csv`,
|
||||
`..._per_seed.csv`, `..._summary.csv`.
|
||||
|
||||
### Comparison with the other conditions (realized)
|
||||
|
||||
| statistic | alpha=0.25 | alpha=0.50 | alpha=0.75 |
|
||||
|---|---|---|---|
|
||||
| class-condition cells with `|S_j| < M` | **19 / 27** | 7 / 27 | **3 / 27** |
|
||||
| missing client-class cells | **38** | 9 | **4** |
|
||||
| client-size ratio mean (seeds) | 14.75 (15.6/20.8/7.8) | 7.41 (5.1/7.2/9.9) | **4.67 (4.15/5.07/4.78)** |
|
||||
| union rare per seed | 8/7/8 | 6/7/7 | 4/5/6 |
|
||||
| union unseen per seed | 6/6/5 | 3/3/1 | 2/1/0 |
|
||||
| mean class-support CV | 1.442 | 1.183 | **0.881** |
|
||||
|
||||
The realized heterogeneity decreases in the expected direction as alpha rises, but **not every
|
||||
per-seed statistic is monotone** (e.g. alpha=0.75 seed 0 has client ratio 4.15 < seed 2's 4.78,
|
||||
and seed 2's max/min for `Lateral_movement` is 1,903). Interpretation uses the realized
|
||||
partitions, not alpha alone.
|
||||
|
||||
---
|
||||
|
||||
## D. Per-seed validation results
|
||||
|
||||
`val rareMacroF1 (pc mean)` is the primary metric; all 10 clients are eligible in every seed.
|
||||
Validation only. Machine-readable:
|
||||
`artifacts/analysis/xiiotid__alpha0.75__multiseed__validation_per_seed.csv`.
|
||||
|
||||
### Seed 0
|
||||
|
||||
| beta | eligible | val rareMacroF1 (pc mean) | val rareMacroF1 (global) | val rareRecall (global) | val macroF1 | val acc |
|
||||
|---|---|---|---|---|---|---|
|
||||
| 0.00 | 10 | 0.496803 | 0.532184 | 0.843412 | 0.747865 | 0.913983 |
|
||||
| 0.25 | 10 | 0.496892 | 0.525361 | 0.832611 | 0.747575 | 0.915125 |
|
||||
| **0.50** | 10 | **0.504388** | 0.519202 | 0.829968 | 0.745780 | 0.914327 |
|
||||
| 0.75 | 10 | 0.486868 | 0.505979 | 0.821332 | 0.738752 | 0.912276 |
|
||||
| 1.00 | 10 | 0.479146 | 0.509581 | 0.839570 | 0.742219 | 0.913479 |
|
||||
|
||||
### Seed 1
|
||||
|
||||
| beta | eligible | val rareMacroF1 (pc mean) | val rareMacroF1 (global) | val rareRecall (global) | val macroF1 | val acc |
|
||||
|---|---|---|---|---|---|---|
|
||||
| 0.00 | 10 | 0.408276 | 0.616818 | 0.885404 | 0.747924 | 0.913234 |
|
||||
| 0.25 | 10 | 0.421386 | 0.628514 | 0.883839 | 0.762087 | 0.929816 |
|
||||
| **0.50** | 10 | **0.422919** | 0.628751 | 0.880953 | 0.763561 | **0.931314** |
|
||||
| 0.75 | 10 | 0.421053 | 0.627215 | 0.877243 | 0.762790 | 0.930295 |
|
||||
| 1.00 | 10 | 0.419534 | 0.624894 | 0.870670 | 0.760871 | 0.928378 |
|
||||
|
||||
### Seed 2
|
||||
|
||||
| beta | eligible | val rareMacroF1 (pc mean) | val rareMacroF1 (global) | val rareRecall (global) | val macroF1 | val acc |
|
||||
|---|---|---|---|---|---|---|
|
||||
| **0.00** | 10 | **0.510038** | 0.674455 | 0.882275 | 0.764538 | 0.933378 |
|
||||
| 0.25 | 10 | 0.504827 | 0.676745 | 0.881395 | 0.766571 | 0.935453 |
|
||||
| 0.50 | 10 | 0.502942 | **0.675491** | 0.876840 | 0.765947 | 0.935232 |
|
||||
| 0.75 | 10 | 0.509702 | 0.675571 | 0.872743 | **0.766351** | **0.935662** |
|
||||
| 1.00 | 10 | 0.507136 | 0.671867 | 0.863907 | 0.765122 | 0.935122 |
|
||||
|
||||
---
|
||||
|
||||
## E. Per-seed diagnostic beta choices (SECONDARY, stability only)
|
||||
|
||||
| seed | selected beta | val rareMacroF1 (pc mean) | tie-break used | test_used_for_selection |
|
||||
|---|---|---|---|---|
|
||||
| 0 | 0.50 | 0.504388 | no | false |
|
||||
| 1 | 0.50 | 0.422919 | no | false |
|
||||
| 2 | 0.00 | 0.510038 | no | false |
|
||||
|
||||
The per-seed preferred beta is more stable than at the other two alphas (two seeds pick 0.50,
|
||||
one picks 0.00). These per-seed choices are **diagnostic only** and are not the condition-level
|
||||
selection rule. `val_selection.json` records `"selection_split": "validation"` and
|
||||
`"test_used_for_selection": false` for all 15 `support_weighted` runs.
|
||||
|
||||
---
|
||||
|
||||
## F. PRIMARY pooled-across-seed validation selection
|
||||
|
||||
| beta | pooled mean | std (sample, ddof=1) | std (pop) | min | max | pooled val rareRecall (pc mean) | selected |
|
||||
|---|---|---|---|---|---|---|---|
|
||||
| 0.00 | 0.471706 | 0.055329 | 0.045176 | 0.408276 | 0.510038 | 0.787289 | |
|
||||
| 0.25 | 0.474368 | 0.046055 | 0.037604 | 0.421386 | 0.504827 | 0.784275 | |
|
||||
| **0.50** | **0.476749** | 0.046624 | 0.038069 | 0.422919 | 0.504388 | 0.786531 | **yes** |
|
||||
| 0.75 | 0.472541 | 0.046028 | 0.037582 | 0.421053 | 0.509702 | 0.780729 | |
|
||||
| 1.00 | 0.468605 | 0.044742 | 0.036532 | 0.419534 | 0.507136 | 0.781309 | |
|
||||
|
||||
- **PRIMARY selected beta (`beta_star_alpha075`) = 0.50.**
|
||||
- **Criterion:** maximum pooled validation per-client-mean rare-class macro-F1.
|
||||
- **Tie-break used:** no (the top two pooled means differ by ≈ 2.4e-3).
|
||||
- **`test_used_for_selection = false`.** Test metrics were not inspected until the pooled beta
|
||||
was fixed.
|
||||
- **Interpretation:** `beta = 0.50` is the *best among the tested candidates under pooled
|
||||
validation across the three project-defined seeds for X-IIoTID alpha=0.75.* It is **not** a
|
||||
global optimum. The pooled validation curve peaks at 0.50 and declines on both sides, but the
|
||||
total between-beta spread (≈ 8.1e-3) is small relative to the between-seed std (≈ 0.045).
|
||||
|
||||
Machine-readable: `artifacts/analysis/xiiotid__alpha0.75__multiseed__validation_pooled.csv`
|
||||
and `...__selection_summary.json`.
|
||||
|
||||
---
|
||||
|
||||
## G. Final selected-beta test metrics (descriptive only)
|
||||
|
||||
`beta_star = 0.50` was fixed from pooled validation; only then were test metrics read.
|
||||
|
||||
| metric (test) | seed 0 | seed 1 | seed 2 | mean ± std (sample) |
|
||||
|---|---|---|---|---|
|
||||
| rare-class macro-F1 | 0.511889 | 0.624144 | 0.679704 | 0.605246 ± 0.085489 |
|
||||
| rare-class recall | 0.803887 | 0.876726 | 0.865681 | 0.848765 ± 0.039256 |
|
||||
| macro-F1 | 0.741977 | 0.761752 | 0.769179 | 0.757636 ± 0.014060 |
|
||||
| accuracy | 0.914365 | 0.932611 | 0.937352 | 0.928110 ± 0.012137 |
|
||||
| weighted-F1 | 0.935566 | 0.948344 | 0.951740 | 0.945216 ± 0.008528 |
|
||||
|
||||
---
|
||||
|
||||
## H. `original_protean` comparison
|
||||
|
||||
| metric (test) | seed 0 | seed 1 | seed 2 | mean ± std (sample) |
|
||||
|---|---|---|---|---|
|
||||
| rare-class macro-F1 | 0.521540 | 0.614061 | 0.676068 | 0.603890 ± 0.077764 |
|
||||
| rare-class recall | 0.816440 | 0.883238 | 0.869835 | 0.856504 ± 0.035338 |
|
||||
| macro-F1 | 0.742471 | 0.747395 | 0.765680 | 0.751849 ± 0.012228 |
|
||||
| accuracy | 0.913254 | 0.913898 | 0.934576 | 0.920576 ± 0.012129 |
|
||||
| weighted-F1 | 0.932563 | 0.935937 | 0.948908 | 0.939136 ± 0.008629 |
|
||||
|
||||
Descriptive difference (`beta_star` − `original_protean`) for test rare-class macro-F1 is
|
||||
−0.009651 (seed 0), +0.010083 (seed 1), +0.003636 (seed 2); mean +0.001356. Seed 0 moves the
|
||||
opposite way to seeds 1–2, and the magnitude is far smaller than the between-seed std
|
||||
(≈ 0.078–0.085). No superiority or generalisation is claimed; this is one dataset, one alpha,
|
||||
three project-defined seeds.
|
||||
|
||||
Test columns are descriptive only and are recorded in
|
||||
`artifacts/analysis/xiiotid__alpha0.75__multiseed__test_descriptive.csv`.
|
||||
|
||||
---
|
||||
|
||||
## I. `beta = 0` equivalence vs `original_protean`
|
||||
|
||||
| property | seed 0 | seed 1 | seed 2 |
|
||||
|---|---|---|---|
|
||||
| same manifest / split / hashes | yes | yes | yes |
|
||||
| round-0 snapshot byte-identical | yes (`8c477df6…`) | yes (`41f0187c…`) | yes (`be2ad5fb…`) |
|
||||
| support/characterization/rare_unseen identical | yes | yes | yes |
|
||||
| independent aggregation diff (`ΣC/n` vs `(1/n)ΣC`) | 4.4e-16 | 4.4e-16 | 2.2e-16 |
|
||||
| history rare-macro-F1 round-0 diff | 0.0 | 0.0 | 0.0 |
|
||||
| history rare-macro-F1 max diff (rounds ≥ 1) | 1.10e-2 | 8.12e-3 | 3.64e-3 |
|
||||
| test metric max diff | 4.33e-3 | 1.14e-3 | 0.85e-3 |
|
||||
| **classification** | **B** | **B** | **B** |
|
||||
|
||||
Class **B**: semantic equivalence + floating-point numerical divergence; **no semantic
|
||||
discrepancy** in any seed. Round 0 is byte-identical; the ~1 ULP ordering difference enters the
|
||||
round-1 prototype-alignment training and the trajectories diverge slowly. Equivalence remains
|
||||
conditional on the shared `S_j` reproduction assumption and is **not** proof that `beta = 0`
|
||||
reproduces original PROTEAN. Machine-readable:
|
||||
`artifacts/analysis/xiiotid__alpha0.75__multiseed__beta0_equivalence.csv`.
|
||||
|
||||
---
|
||||
|
||||
## J. Direct prototype-effect findings (fixed round-0 snapshots, no retraining)
|
||||
|
||||
Computed with the production aggregation from each seed's fixed `{C_ij, N_ij}` round-0
|
||||
snapshot. `||Cbar_j(beta) - Cbar_j(0)||` at `beta = 1.0`, cross-seed mean (sample std):
|
||||
|
||||
| class | mean disp | std | mean rel disp |
|
||||
|---|---|---|---|
|
||||
| Tampering | 1.934 | 0.427 | 0.397 |
|
||||
| Weaponization | 1.472 | 0.170 | 0.235 |
|
||||
| Exfiltration | 1.448 | 0.086 | 0.207 |
|
||||
| Exploitation | 1.539 | 0.252 | 0.284 |
|
||||
| Lateral_movement | 1.369 | 0.553 | 0.262 |
|
||||
| C&C | 1.284 | 0.543 | 0.262 |
|
||||
| Reconnaissance | 0.983 | 0.412 | 0.171 |
|
||||
| Normal | 0.903 | 0.298 | 0.162 |
|
||||
| RDOS | 0.814 | 0.200 | 0.096 |
|
||||
|
||||
- Mean displacement across the nine classes is **1.305**, far smaller than at alpha=0.50 (2.099)
|
||||
and alpha=0.25 (3.422), consistent with the lower support imbalance at alpha=0.75.
|
||||
- The most support-imbalanced classes (`Tampering` CV ≈ 1.0–1.2, `Weaponization`,
|
||||
`Exfiltration`) move most; `RDOS` and `Normal` move least in relative terms.
|
||||
- Displacement is a **direct-aggregation measure only** and is not interpreted as improved or
|
||||
degraded detection. The end-to-end effect (§F/§G) is reported separately.
|
||||
|
||||
Outputs: `artifacts/analysis/xiiotid__alpha0.75__seed{0,1,2}__support_weighted__beta0__prototype_snapshot__prototype_effect.csv`
|
||||
and `...__prototype_weights.csv`; cross-seed aggregate
|
||||
`artifacts/analysis/xiiotid__alpha0.75__multiseed__prototype_effect_pooled.csv`.
|
||||
|
||||
---
|
||||
|
||||
## K. Client-level effect (validation, relative to beta = 0)
|
||||
|
||||
Full per-client table:
|
||||
`artifacts/analysis/xiiotid__alpha0.75__multiseed__client_validation_detail.csv`; summary:
|
||||
`...__client_validation_summary.csv`.
|
||||
|
||||
| seed | beta | improve | degrade | unchanged | mean Δ | min Δ | max Δ |
|
||||
|---|---|---|---|---|---|---|---|
|
||||
| 0 | 0.25 | 5 | 5 | 0 | +0.0001 | −0.0192 | +0.0269 |
|
||||
| 0 | 0.50 | 6 | 4 | 0 | +0.0076 | −0.0361 | +0.0480 |
|
||||
| 0 | 0.75 | 3 | 7 | 0 | −0.0099 | −0.0433 | +0.0253 |
|
||||
| 0 | 1.00 | 1 | 9 | 0 | −0.0177 | −0.0650 | +0.0222 |
|
||||
| 1 | 0.25 | 9 | 0 | 1 | +0.0131 | 0.0000 | +0.0318 |
|
||||
| 1 | 0.50 | 9 | 0 | 1 | +0.0146 | 0.0000 | +0.0402 |
|
||||
| 1 | 0.75 | 9 | 0 | 1 | +0.0128 | 0.0000 | +0.0375 |
|
||||
| 1 | 1.00 | 7 | 2 | 1 | +0.0113 | −0.0116 | +0.0578 |
|
||||
| 2 | 0.25 | 7 | 3 | 0 | −0.0052 | −0.1212 | +0.0382 |
|
||||
| 2 | 0.50 | 6 | 4 | 0 | −0.0071 | −0.1524 | +0.0478 |
|
||||
| 2 | 0.75 | 5 | 5 | 0 | −0.0003 | −0.0860 | +0.0531 |
|
||||
| 2 | 1.00 | 6 | 4 | 0 | −0.0029 | −0.1212 | +0.0531 |
|
||||
|
||||
Descriptive observations:
|
||||
|
||||
- The response is seed-dependent. At the selected `beta = 0.50`, seed 1 improves on 9/10
|
||||
clients (mean +0.0146), seed 0 on 6/10 (mean +0.0076), and seed 2 on 6/10 but with a negative
|
||||
mean (−0.0071) driven by one client at −0.152.
|
||||
- The `beta = 0.50` deltas are much smaller in magnitude than at alpha=0.25 or alpha=0.50,
|
||||
reflecting the smaller direct displacement (§J).
|
||||
- Client ids are per-seed realisations and are not treated as one population. This analysis is
|
||||
descriptive and non-causal; `N_ij` vs ΔF1 is non-monotonic.
|
||||
|
||||
---
|
||||
|
||||
## L. Runtime and resources
|
||||
|
||||
CPU only, no GPU, no swap, exit status 0 for every run (`/usr/bin/time -v`).
|
||||
|
||||
| seed | tag | wall | CPU % | peak RSS |
|
||||
|---|---|---|---|---|
|
||||
| 0 | `original_protean` | 40:40.74 | 745 | 6.49 GiB |
|
||||
| 0 | beta 0.00 | 40:04.93 | 746 | 6.49 GiB |
|
||||
| 0 | beta 0.25 | 40:50.34 | 745 | 6.49 GiB |
|
||||
| 0 | beta 0.50 | 40:48.88 | 746 | 6.49 GiB |
|
||||
| 0 | beta 0.75 | 40:48.60 | 746 | 6.49 GiB |
|
||||
| 0 | beta 1.00 | 40:09.82 | 745 | 6.49 GiB |
|
||||
| 1 | `original_protean` | 40:25.70 | 745 | 6.91 GiB |
|
||||
| 1 | beta 0.00 | 40:00.25 | 745 | 6.91 GiB |
|
||||
| 1 | beta 0.25 | 40:10.91 | 745 | 6.91 GiB |
|
||||
| 1 | beta 0.50 | 40:16.31 | 745 | 6.91 GiB |
|
||||
| 1 | beta 0.75 | 40:18.58 | 744 | 6.91 GiB |
|
||||
| 1 | beta 1.00 | 49:01.62 | 714 | 6.91 GiB |
|
||||
| 2 | `original_protean` | 40:18.15 | 745 | 7.20 GiB |
|
||||
| 2 | beta 0.00 | 40:31.08 | 745 | 7.20 GiB |
|
||||
| 2 | beta 0.25 | 40:18.53 | 745 | 7.20 GiB |
|
||||
| 2 | beta 0.50 | 43:17.28 | 732 | 7.20 GiB |
|
||||
| 2 | beta 0.75 | 41:01.74 | 744 | 7.20 GiB |
|
||||
| 2 | beta 1.00 | 40:27.57 | 745 | 7.20 GiB |
|
||||
|
||||
- New compute this session: **18 runs, 44,371 s ≈ 12.33 h wall-clock**, sequential on an
|
||||
8-core host.
|
||||
- Peak RSS is partition-dependent, not beta-dependent: 6.49 GiB (seed 0), 6.91 GiB (seed 1),
|
||||
7.20 GiB (seed 2); all well within the 29 GiB host. Two runs were slightly slower
|
||||
(seed 1 beta 1.00, seed 2 beta 0.50) due to transient host contention; both exited 0.
|
||||
- No warnings, no client failures, 9/9 global prototypes in every round, no retries.
|
||||
- Machine-readable: `artifacts/analysis/xiiotid__alpha0.75__multiseed__runtime.csv`.
|
||||
|
||||
---
|
||||
|
||||
## M. Limitations
|
||||
|
||||
- **One dataset** (X-IIoTID). No cross-dataset conclusion.
|
||||
- **Three project-defined seeds** (`{0,1,2}`); the pooled mean's standard error is of the same
|
||||
order as the between-beta spread, so the selected beta is statistically weak.
|
||||
- The `S_j` participant/denominator rule
|
||||
(`S_j = {i | N_ij > 0 and valid C_ij}`, equal weights in the baseline) remains a
|
||||
**REPRODUCTION ASSUMPTION**. At alpha=0.75 it is material in only **3/27** class-condition
|
||||
cells, but the `beta = 0` comparison is still conditional on both modes sharing this rule and
|
||||
does **not** prove `beta = 0` reproduces original PROTEAN.
|
||||
- Train/validation/test adaptation (70/10/20 stratified) differs from the paper's literal
|
||||
80/20; the validation eval partition is a project decision.
|
||||
- **No 5G-NIDD beta result.**
|
||||
- **No global beta optimum claim.** `beta = 0.50` is only the best among the five tested
|
||||
candidates under pooled validation for X-IIoTID alpha=0.75 across seeds `{0,1,2}`.
|
||||
- The union of rare classes (and hence global rare support) differs by seed and by alpha;
|
||||
only the per-client-mean metric is directly comparable within a condition.
|
||||
- Test metrics of the selected beta are single-condition and must not be read as
|
||||
generalisation; no test metric influenced selection.
|
||||
@@ -0,0 +1,268 @@
|
||||
# Session 8 Post-Experiment Audit (X-IIoTID alpha=0.75)
|
||||
|
||||
Status: **PASS.** Independent recomputation from machine-readable artifacts confirms every
|
||||
Session 8 claim. No discovered issue changes `beta_star` or the scientific interpretation. No
|
||||
corrections were required. **No training was run, no aggregation/model source changed, no
|
||||
test-based selection occurred.**
|
||||
|
||||
Audit performed: 2026-09-26. Audited HEAD: `ff68d380e23859d21c07c8a3a7b56b1b7f06c91b`.
|
||||
|
||||
Companion documents: `docs/research/ALPHA075_BETA_VALIDATION.md`,
|
||||
`docs/research/XIIOTID_CROSS_ALPHA_ANALYSIS.md`, `docs/research/EXPERIMENT_PROTOCOL.md`,
|
||||
`docs/handoff/SESSION_HANDOFF.md`.
|
||||
|
||||
---
|
||||
|
||||
## A. Scope
|
||||
|
||||
Independently verify the Session 8 claim for:
|
||||
|
||||
- dataset `xiiotid`, alpha `0.75`, seeds `{0,1,2}`, beta `{0, 0.25, 0.5, 0.75, 1.0}` plus
|
||||
`original_protean` (18 runs);
|
||||
- PRIMARY pooled-validation selection `beta_star = 0.50`, using validation per-client
|
||||
rare-class macro-F1 averaged within seed then across seeds;
|
||||
- cross-alpha labels (alpha=0.25 → 0.00, alpha=0.50 → 0.75, alpha=0.75 → 0.50).
|
||||
|
||||
The audit recomputed from run artifacts and re-derived selection; it repeated no training and
|
||||
ran no new condition.
|
||||
|
||||
---
|
||||
|
||||
## B. Run inventory
|
||||
|
||||
18 full-data runs enumerated from `results/*/metadata.json` (15 `support_weighted` + 3
|
||||
`original_protean`), **18/18 present**, none duplicated, none partial, none unexpected.
|
||||
|
||||
- Metadata verified per run: dataset=xiiotid, alpha=0.75, seed, aggregation mode, beta,
|
||||
clients=10, rounds=10, local_epochs=3, batch=256, lr=1e-3, mu=0.1, lambda=1.0,
|
||||
`manifest_reload_ok=true`, `smoke=false`.
|
||||
- All 14 expected artifacts present for every run; the round-0 snapshot exists for every run.
|
||||
- No run exists for any alpha ≠ 0.75 in this session; **no 5G-NIDD `support_weighted` run**
|
||||
exists; `equal_available` absent from `src/`, `scripts/`, `tests/`.
|
||||
|
||||
---
|
||||
|
||||
## C. Pairing / manifest integrity
|
||||
|
||||
Within each seed, all six runs share one manifest content hash and a byte-identical round-0
|
||||
snapshot (SHA-256):
|
||||
|
||||
| seed | manifest content hash | round-0 snapshot SHA-256 | support/char/rare_unseen |
|
||||
|---|---|---|---|
|
||||
| 0 | `759f7e504a7d442101238726334d121a746ea4a8ff366428c1c174e47f358723` | `8c477df6b3af645bf2db1c8005d86ea6258b283370ff3ef3e6e88d6f40095564` | identical |
|
||||
| 1 | `4a50ba219de20af14f6ad73976111659fba2d5b25cd5eeb1a2f21b76de0d9303` | `41f0187c4f0a8e3db0a8ab7eff0aa50a8f3e4a64ded2448228bd133ea017869d` | identical |
|
||||
| 2 | `922b7bb15169302be7dd4d4eb1644d077537872e1e91fe59b7525b7e3343cc1c` | `be2ad5fb5fcf87c49b2826936c8d5dae6cdc4ab25fe2677081acec32f8116648` | identical |
|
||||
|
||||
Each manifest was independently reproduced from the raw dataset (`prepare_dataset` →
|
||||
`reproduce_train_assignments`): all three seeds return exact `N_ij` match, partition-hash match,
|
||||
split sizes 569,909 / 81,414 / 162,831, `N_ij` sum 569,909, 10 clients. The split hash is
|
||||
identical across alpha for a given seed (splits are per dataset-seed); the partition hash
|
||||
differs, as it must. Pairing is proven by content hashes, not filenames.
|
||||
|
||||
---
|
||||
|
||||
## D. Partition characterization audit
|
||||
|
||||
Independently recomputed from the manifests. Matches the report exactly:
|
||||
|
||||
| statistic | alpha=0.75 seed 0 / 1 / 2 | reality (sum) |
|
||||
|---|---|---|
|
||||
| `|S_j| < M` cells | 2 / 1 / 0 | **3 / 27** |
|
||||
| missing client-class cells | 3 / 1 / 0 | **4** |
|
||||
| client-size ratio | 4.15 / 5.07 / 4.78 | mean **4.67** |
|
||||
| union unseen classes | 2 / 1 / 0 | max 1 on a client |
|
||||
| union rare classes | 4 / 5 / 6 | 2 rare per client (all) |
|
||||
|
||||
Cross-alpha comparison confirmed: alpha=0.25 = 19/27 cells / 38 missing; alpha=0.50 = 7/27 / 9.
|
||||
Interpretation uses realized statistics, not alpha alone.
|
||||
|
||||
---
|
||||
|
||||
## E. Validation metric recomputation
|
||||
|
||||
Recomputed from raw artifacts (no report numbers copied):
|
||||
|
||||
- seed-level primary score = mean over eligible clients of `val_per_client.csv`
|
||||
`rare_class_macro_f1`; equals `val_selection.json` per-client-mean to **< 1e-12** for all 15
|
||||
runs;
|
||||
- global validation accuracy / macro-F1 / weighted-F1 / rare macro-F1 / rare recall recomputed
|
||||
independently from `val_confusion_matrix.json` with the production formulas: **max diff 0.0**
|
||||
versus `val_global_metrics.json`.
|
||||
|
||||
All 10 clients are eligible in every seed/beta. Per-seed diagnostics reproduce **0.50 / 0.50 /
|
||||
0.00**.
|
||||
|
||||
---
|
||||
|
||||
## F. Rare / unseen integrity
|
||||
|
||||
Per-client rare classes recomputed from training `N_ij` (two smallest positive-support attack
|
||||
classes, tie by class id) and compared to `rare_unseen.csv` flags/N_ij across all 18 runs:
|
||||
|
||||
- **1,620 cells checked, 0 mismatches.**
|
||||
- Benign class (`Normal`) never flagged rare/unseen; rare and unseen never overlap.
|
||||
- Union training-derived rare classes equal the run's `evaluated_rare_classes`; validation/test
|
||||
labels did not influence rare identity.
|
||||
- Every client has exactly two rare classes.
|
||||
|
||||
---
|
||||
|
||||
## G. Pooled-selection recomputation
|
||||
|
||||
Computed from the independently recomputed seed-level scores (not from the report). Pooled =
|
||||
mean of the three seed means; std sample (`ddof=1`).
|
||||
|
||||
| beta | pooled mean | sample std | min | max |
|
||||
|---|---|---|---|---|
|
||||
| 0.00 | 0.471706 | 0.055329 | 0.408276 | 0.510038 |
|
||||
| 0.25 | 0.474368 | 0.046055 | 0.421386 | 0.504827 |
|
||||
| **0.50** | **0.476749** | 0.046624 | 0.422919 | 0.504388 |
|
||||
| 0.75 | 0.472541 | 0.046028 | 0.421053 | 0.509702 |
|
||||
| 1.00 | 0.468605 | 0.044742 | 0.419534 | 0.507136 |
|
||||
|
||||
- Recompute **matches the report** to formatting precision.
|
||||
- `argmax` = **0.50** (no tie; top-two gap ≈ 2.4e-3). `tie_break_used=false`.
|
||||
|
||||
---
|
||||
|
||||
## H. Validation / test leakage audit
|
||||
|
||||
- `run_baseline.py` derives `union_rare` from the training support matrix only; the
|
||||
`val_selection` payload is built only from validation artifacts, and `test_used_for_selection`
|
||||
/ `selection_split` are recorded for all 15 `support_weighted` runs.
|
||||
- `analyze_multiseed_beta.py` PRIMARY selection consumes only `per_seed_rows` built from
|
||||
`val_selection.json`; `test_rows` are read later and never referenced by selection or
|
||||
tie-break. No code path sorts/filters candidates by a test field.
|
||||
- The audit's own `beta_star = 0.50` was reproduced from validation artifacts alone.
|
||||
|
||||
Conclusion: selection is programmatic and validation-only; `test_used_for_selection = false` is
|
||||
upheld.
|
||||
|
||||
---
|
||||
|
||||
## I. Final test recomputation
|
||||
|
||||
`beta_star = 0.50` fixed from pooled validation; only then test metrics read. Recomputed
|
||||
independently from `test_confusion_matrix.json` (diff vs JSON = 0.0), then averaged across seeds
|
||||
with sample std:
|
||||
|
||||
| metric | selected beta 0.50 (mean ± std) | original_protean (mean ± std) |
|
||||
|---|---|---|
|
||||
| rare-class macro-F1 | 0.605246 ± 0.085489 | 0.603890 ± 0.077764 |
|
||||
| rare-class recall | 0.848765 ± 0.039256 | 0.856504 ± 0.035338 |
|
||||
| macro-F1 | 0.757636 ± 0.014060 | 0.751849 ± 0.012228 |
|
||||
| accuracy | 0.928110 ± 0.012137 | 0.920576 ± 0.012129 |
|
||||
| weighted-F1 | 0.945216 ± 0.008528 | 0.939136 ± 0.008629 |
|
||||
|
||||
Matches the report exactly. No superiority claim is made.
|
||||
|
||||
---
|
||||
|
||||
## J. beta = 0 equivalence audit
|
||||
|
||||
For seeds 0, 1, 2, `original_protean` vs `support_weighted beta=0`:
|
||||
|
||||
| property | seed 0 | seed 1 | seed 2 |
|
||||
|---|---|---|---|
|
||||
| same manifest / split / hashes | yes | yes | yes |
|
||||
| round-0 snapshot byte-identical | yes | yes | yes |
|
||||
| support/characterization/rare_unseen identical | yes | yes | yes |
|
||||
| independent aggregation diff (`ΣC/n` vs `(1/n)ΣC`) | 4.4e-16 | 4.4e-16 | 2.2e-16 |
|
||||
| history rare-macro-F1 round-0 diff | 0.0 | 0.0 | 0.0 |
|
||||
| history rare-macro-F1 max diff (rounds ≥ 1) | 1.10e-2 | 8.12e-3 | 3.64e-3 |
|
||||
| test metric max diff | 4.33e-3 | 1.14e-3 | 0.85e-3 |
|
||||
| classification | **B** | **B** | **B** |
|
||||
|
||||
Class **B** (semantically equivalent + floating-point divergence); **no semantic discrepancy**.
|
||||
Equivalence remains conditional on the shared `S_j` reproduction assumption.
|
||||
|
||||
---
|
||||
|
||||
## K. Direct-effect audit
|
||||
|
||||
Independently recomputed `||Cbar_j(beta) − Cbar_j(0)||` from the fixed round-0 snapshot with a
|
||||
hand-rolled NumPy aggregation: max absolute difference vs the per-seed
|
||||
`...__prototype_effect.csv` = **8.9e-16** (seed 0 check across all classes/betas). Cross-seed
|
||||
mean displacement at `beta=1`: **1.305** (alpha=0.75) vs 2.099 (alpha=0.50) and 3.422
|
||||
(alpha=0.25). Displacement is a direct-aggregation measure only; no detection causality is
|
||||
inferred.
|
||||
|
||||
---
|
||||
|
||||
## L. Client-level audit
|
||||
|
||||
Deltas recomputed from `val_per_client.csv` vs the `client_validation_detail.csv` deltas:
|
||||
**max absolute difference 0.0** across all seeds/betas/clients. At the selected
|
||||
`beta=0.50`: 6/4/0 (seed 0, mean +0.008), 9/0/1 (seed 1, +0.015), 6/4/0 (seed 2, −0.007).
|
||||
`N_ij` vs ΔF1 is non-monotonic. Client ids are per-seed realisations, not pooled.
|
||||
|
||||
---
|
||||
|
||||
## M. Cross-alpha audit
|
||||
|
||||
Condition-level **pooled** selections confirmed from `cross_alpha_summary.json`:
|
||||
|
||||
| condition | selected beta | tie-break | test_used_for_selection |
|
||||
|---|---|---|---|
|
||||
| alpha=0.25 | 0.00 | no | false |
|
||||
| alpha=0.50 | 0.75 | no | false |
|
||||
| alpha=0.75 | 0.50 | no | false |
|
||||
|
||||
The sequence 0.00 → 0.75 → 0.50 is **not monotone**. No document in the repository states a
|
||||
monotone alpha→beta trend. The report explicitly refuses a monotonic interpretation.
|
||||
|
||||
---
|
||||
|
||||
## N. Artifact provenance
|
||||
|
||||
| Reported quantity | Source artifact(s) | Derivation |
|
||||
|---|---|---|
|
||||
| run existence / config | `results/<run>/metadata.json` | direct read |
|
||||
| manifest hashes / reproduction | `artifacts/partitions/xiiotid__alpha0.75__seed{0,1,2}.json` | module + `reproduce_train_assignments` |
|
||||
| pairing proof | `artifacts/analysis/...__prototype_snapshot.json` | sha256 across 6 runs/seed |
|
||||
| seed-level validation score | `results/.../val_per_client.csv` + `val_selection.json` | mean of per-client rare macro-F1 |
|
||||
| validation global metrics | `results/.../val_confusion_matrix.json` | independent numpy recompute |
|
||||
| pooled mean/std, `beta_star` | recomputed seed scores | mean/`stdev`, argmax |
|
||||
| test metrics | `results/.../test_confusion_matrix.json` | independent recompute + mean/std |
|
||||
| beta=0 equivalence | original vs beta0 artifacts/snapshots | sha256 + independent aggregation + history diff |
|
||||
| direct-effect displacement | snapshots + `...__prototype_effect_pooled.csv` | independent numpy recompute |
|
||||
| client improve/degrade | `results/.../val_per_client.csv` | deltas vs beta=0 |
|
||||
| rare-class identity | `results/.../rare_unseen.csv` + manifest | recompute definition |
|
||||
| partition characterization | manifests + heterogeneity CSVs | independent numpy recompute |
|
||||
| runtime / RSS | `artifacts/analysis/xiiotid__alpha0.75__multiseed__runtime.csv` (source `/tmp/opencode/s8_alpha075/logs/*.time`, present) | parse `/usr/bin/time -v`; sum 44,371 s = 12.33 h |
|
||||
| cross-alpha table | `artifacts/analysis/xiiotid__cross_alpha__*` | read per-condition multiseed artifacts |
|
||||
|
||||
---
|
||||
|
||||
## O. Deviations / corrections found
|
||||
|
||||
**None.** No arithmetic, metric-label, std-convention, provenance or pairing defect was found in
|
||||
the Session 8 report or analysis artifacts. The three new read-only analysis scripts
|
||||
(`analyze_partition_heterogeneity.py`, `verify_beta0_equivalence.py`, `analyze_cross_alpha.py`)
|
||||
do not touch training or aggregation source.
|
||||
|
||||
Minor note (informational, not a defect): two runs were slower than 41 min (seed 1 beta 1.00 at
|
||||
49:02, seed 2 beta 0.50 at 43:17) due to transient host contention; all 18 exited 0.
|
||||
|
||||
---
|
||||
|
||||
## P. Final audit verdict
|
||||
|
||||
**PASS.**
|
||||
|
||||
- Run inventory: **PASS** (18/18; no duplicates/partials; no alpha≠0.75 or 5G-NIDD run).
|
||||
- Pairing / manifest reproduction: **PASS** (hash-identical; raw-data reproduction exact).
|
||||
- Partition characterization: **PASS** (3/27, 4, 4.15/5.07/4.78, unseen 2/1/0).
|
||||
- Validation recomputation (seed-level and global): **PASS** (exact).
|
||||
- Rare/unseen integrity: **PASS** (0 mismatches over 1,620 cells).
|
||||
- Pooled selection: **PASS**; independent `beta_star = 0.50` using validation only.
|
||||
- Validation/test leakage: **PASS**.
|
||||
- Test summaries: **PASS** (exact).
|
||||
- beta=0 equivalence: **PASS**, class **B** for all seeds.
|
||||
- Direct-effect and client-level analyses: **PASS** (independent recompute exact).
|
||||
- Cross-alpha labels: **PASS** (0.00 / 0.75 / 0.50; not monotone; no monotone claim).
|
||||
- Source/data integrity: **PASS**; pytest 75 passed.
|
||||
|
||||
Session 8 is **safe to checkpoint** with the documented limitations (single dataset, three
|
||||
alphas, three project-defined seeds, weak effect relative to seed variance, `S_j` reproduction
|
||||
assumption, no global-optimum claim).
|
||||
@@ -0,0 +1,223 @@
|
||||
# X-IIoTID Cross-Alpha Analysis (alpha = 0.25 / 0.50 / 0.75)
|
||||
|
||||
Status: **descriptive three-condition comparison** of the frozen beta protocol on X-IIoTID,
|
||||
using the audited condition-level pooled results of Sessions 6 (`alpha=0.50`), 7
|
||||
(`alpha=0.25`) and 8 (`alpha=0.75`). This document does **not** run anything and does not
|
||||
make a causal or monotonicity claim. Machine-readable counterpart:
|
||||
`artifacts/analysis/xiiotid__cross_alpha__cross_alpha_beta_table.csv`, `..._summary.json`,
|
||||
`..._displacement.csv`, `..._client_summary.csv`, and
|
||||
`artifacts/analysis/xiiotid__cross_alpha__partition_heterogeneity_*.csv`.
|
||||
|
||||
Companion documents: `docs/research/ALPHA075_BETA_VALIDATION.md`,
|
||||
`docs/research/ALPHA025_BETA_VALIDATION.md`, `docs/research/MULTISEED_BETA_VALIDATION.md`,
|
||||
`docs/research/EXPERIMENT_PROTOCOL.md`, `docs/handoff/SESSION_HANDOFF.md`.
|
||||
|
||||
---
|
||||
|
||||
## A. Experimental scope
|
||||
|
||||
| Field | Value |
|
||||
|---|---|
|
||||
| dataset | X-IIoTID (`xiiotid`) |
|
||||
| alpha | 0.25, 0.50, 0.75 |
|
||||
| seeds | 0, 1, 2 |
|
||||
| betas | 0.00, 0.25, 0.50, 0.75, 1.00 |
|
||||
| aggregation | `original_protean` + `support_weighted` |
|
||||
| selection | pooled validation-only per condition, seeds `{0,1,2}` |
|
||||
| test | read only after each condition's pooled beta is fixed |
|
||||
|
||||
All three conditions share the frozen training protocol: 10 clients, 10 rounds, 3 local epochs,
|
||||
batch 256, Adam `lr=1e-3`, `mu=0.1`, `lambda=1.0`, unchanged architecture/preprocessing/split
|
||||
recipe/loss/inference. For each `(alpha, seed)` all six runs share one manifest and a
|
||||
byte-identical round-0 snapshot.
|
||||
|
||||
---
|
||||
|
||||
## B. Realized heterogeneity
|
||||
|
||||
`|S_j| < M` counts class-condition cells with fewer than 10 contributing clients, summed over
|
||||
the three seeds (out of 27). Missing cells count `(client, class)` pairs with `N_ij = 0`.
|
||||
|
||||
| statistic | alpha=0.25 | alpha=0.50 | alpha=0.75 |
|
||||
|---|---|---|---|
|
||||
| `|S_j| < M` cells (sum over 3 seeds) | **19 / 27** | 7 / 27 | **3 / 27** |
|
||||
| missing client-class cells | **38** | 9 | **4** |
|
||||
| client-size ratio (seed 0/1/2) | 15.6 / 20.8 / 7.8 | 5.1 / 7.2 / 9.9 | 4.15 / 5.07 / 4.78 |
|
||||
| client-size ratio mean | 14.75 | 7.41 | **4.67** |
|
||||
| union rare classes per seed | 8 / 7 / 8 | 6 / 7 / 7 | 4 / 5 / 6 |
|
||||
| union unseen classes per seed | 6 / 6 / 5 | 3 / 3 / 1 | 2 / 1 / 0 |
|
||||
| max unseen classes on a client | 4 | 2 | 1 |
|
||||
| mean class-support CV | 1.442 | 1.183 | **0.881** |
|
||||
| max per-class max/min ratio (over seeds) | 46,541 | 6,204 | 1,903 |
|
||||
|
||||
Realized heterogeneity decreases as alpha rises, but **not uniformly per seed** (e.g. at
|
||||
alpha=0.75 seed 0 the client ratio 4.15 is lower than seed 2's 4.78; alpha=0.50 seed 2's ratio
|
||||
9.9 exceeds alpha=0.25 seed 2's 7.8). Interpretation uses these realized partitions, not alpha
|
||||
alone.
|
||||
|
||||
---
|
||||
|
||||
## C. Pooled validation curves (alpha × beta)
|
||||
|
||||
Pooled validation per-client-mean rare-class macro-F1 (selection metric; validation only):
|
||||
|
||||
| beta | alpha=0.25 mean (std) | alpha=0.50 mean (std) | alpha=0.75 mean (std) |
|
||||
|---|---|---|---|
|
||||
| 0.00 | **0.591704** (0.089529) | 0.544361 (0.091447) | 0.471706 (0.055329) |
|
||||
| 0.25 | 0.588691 (0.066435) | 0.555434 (0.090068) | 0.474368 (0.046055) |
|
||||
| 0.50 | 0.585851 (0.044858) | 0.567322 (0.088539) | **0.476749** (0.046624) |
|
||||
| 0.75 | 0.579463 (0.064906) | **0.579367** (0.075121) | 0.472541 (0.046028) |
|
||||
| 1.00 | 0.532099 (0.045718) | 0.573479 (0.100450) | 0.468605 (0.044742) |
|
||||
| **curve shape** | monotone decreasing | rises to peak at 0.75 | peaks at 0.50, declines both sides |
|
||||
| **total between-beta spread** | 0.0596 | 0.0350 | **0.0081** |
|
||||
|
||||
The across-seed sample std (0.045–0.100) is comparable to or larger than the between-beta
|
||||
spread at every alpha, so these selections are statistically weak descriptions, not strong
|
||||
preferences.
|
||||
|
||||
---
|
||||
|
||||
## D. Selected beta by condition
|
||||
|
||||
Condition-level **pooled** selections only (per-seed diagnostics are excluded):
|
||||
|
||||
| condition | pooled-selected beta | pooled validation mean | tie-break used |
|
||||
|---|---|---|---|
|
||||
| alpha=0.25 | **0.00** | 0.591704 | no |
|
||||
| alpha=0.50 | **0.75** | 0.579367 | no |
|
||||
| alpha=0.75 | **0.50** | 0.476749 | no |
|
||||
|
||||
The selected beta **changes with the non-IID condition but is not monotone** in alpha
|
||||
(0.00 → 0.75 → 0.50). The value 0.50 at alpha=0.50 is only the Session-5 seed-0 choice and the
|
||||
Session-6 per-seed diagnostic for seed 0; it is **not** the alpha=0.50 pooled selection.
|
||||
|
||||
---
|
||||
|
||||
## E. Final test summaries (descriptive)
|
||||
|
||||
Selected beta vs `original_protean`, mean ± sample std across seeds `{0,1,2}`.
|
||||
|
||||
| condition | selected beta | test rare macro-F1 (selected) | test rare macro-F1 (original) | test macro-F1 (selected) | test macro-F1 (original) | test acc (selected) | test acc (original) |
|
||||
|---|---|---|---|---|---|---|---|
|
||||
| alpha=0.25 | 0.00 | 0.632136 ± 0.047642 | 0.632790 ± 0.047152 | 0.681343 ± 0.020555 | 0.682018 ± 0.020967 | 0.874015 ± 0.010267 | 0.875431 ± 0.009067 |
|
||||
| alpha=0.50 | 0.75 | 0.665503 ± 0.026685 | 0.642520 ± 0.028683 | 0.731169 ± 0.006234 | 0.708965 ± 0.001172 | 0.906392 ± 0.018450 | 0.899454 ± 0.008398 |
|
||||
| alpha=0.75 | 0.50 | 0.605246 ± 0.085489 | 0.603890 ± 0.077764 | 0.757636 ± 0.014060 | 0.751849 ± 0.012228 | 0.928110 ± 0.012137 | 0.920576 ± 0.012129 |
|
||||
|
||||
**Do not compare the absolute test rare-class macro-F1 across conditions**: the training-derived
|
||||
union of rare classes (and hence the global rare evaluation support) differs by alpha and seed
|
||||
(e.g. alpha=0.75 test rare support 6,251 / 34,503 / 25,454). Only the selected-vs-original
|
||||
difference *within* a condition is meaningful, and even that is dominated by between-seed
|
||||
variance. No superiority or generalisation is claimed.
|
||||
|
||||
---
|
||||
|
||||
## F. Direct prototype displacement (beta = 1 vs beta = 0)
|
||||
|
||||
Cross-seed mean `||Cbar_j(1) − Cbar_j(0)||` on the fixed round-0 snapshots (no retraining):
|
||||
|
||||
| class | alpha=0.25 | alpha=0.50 | alpha=0.75 |
|
||||
|---|---|---|---|
|
||||
| Tampering | 4.248 | 2.354 | 1.934 |
|
||||
| Exfiltration | 4.316 | 2.020 | 1.448 |
|
||||
| Exploitation | 3.464 | 2.344 | 1.539 |
|
||||
| Lateral_movement | 3.726 | 2.724 | 1.369 |
|
||||
| C&C | 4.020 | 1.694 | 1.284 |
|
||||
| Weaponization | 3.124 | 2.561 | 1.472 |
|
||||
| Reconnaissance | 3.339 | 1.002 | 0.983 |
|
||||
| Normal | 1.997 | 1.557 | 0.903 |
|
||||
| RDOS | 2.566 | 2.631 | 0.814 |
|
||||
| **mean across classes** | **3.422** | **2.099** | **1.305** |
|
||||
|
||||
Mean displacement tracks realized support imbalance (alpha=0.25 > 0.50 > 0.75). The per-seed
|
||||
rank order of classes is seed-sensitive at every alpha. Displacement is a direct-aggregation
|
||||
measure only; it is **not** interpreted as improved or degraded detection.
|
||||
|
||||
---
|
||||
|
||||
## G. Client-level behaviour
|
||||
|
||||
Improve/degrade/unchanged counts (validation, relative to `beta = 0`).
|
||||
|
||||
At each condition's pooled-selected beta:
|
||||
|
||||
| condition | selected beta | seed 0 | seed 1 | seed 2 |
|
||||
|---|---|---|---|---|
|
||||
| alpha=0.25 | 0.00 | 0/0/10 (trivial) | 0/0/10 (trivial) | 0/0/10 (trivial) |
|
||||
| alpha=0.50 | 0.75 | 7/3/0 (+0.021) | 8/1/1 (+0.027) | 8/1/1 (+0.058) |
|
||||
| alpha=0.75 | 0.50 | 6/4/0 (+0.008) | 9/0/1 (+0.015) | 6/4/0 (−0.007) |
|
||||
|
||||
(mean Δ in parentheses.) At a common `beta = 0.75`:
|
||||
|
||||
| condition | seed 0 | seed 1 | seed 2 |
|
||||
|---|---|---|---|
|
||||
| alpha=0.25 | 5/4/1 | 5/4/1 | 3/5/2 |
|
||||
| alpha=0.50 | 7/3/0 | 8/1/1 | 8/1/1 |
|
||||
| alpha=0.75 | 3/7/0 | 9/0/1 | 5/5/0 |
|
||||
|
||||
The client-level response is seed-dependent at every alpha. `N_ij` vs ΔF1 is non-monotonic
|
||||
everywhere. Client ids are per-seed realisations and are never pooled across seeds.
|
||||
|
||||
---
|
||||
|
||||
## H. Relation to RQ1 (support imbalance ↔ displacement ↔ rare-class performance)
|
||||
|
||||
Observed, descriptive:
|
||||
|
||||
- Realized support imbalance decreases with alpha (mean class CV 1.442 / 1.183 / 0.881;
|
||||
`|S_j| < M` cells 19 / 7 / 3), and mean prototype displacement decreases with it
|
||||
(3.422 / 2.099 / 1.305). Directionally consistent across the three conditions.
|
||||
- Rare-class validation *levels* do **not** follow the same ordering (pooled means ≈ 0.59 /
|
||||
0.56–0.58 / 0.47). Absolute cross-condition levels are not controlled because the
|
||||
training-derived rare-class sets and per-client eval partitions differ.
|
||||
|
||||
**No causal conclusion** is drawn: the association between support imbalance and displacement is
|
||||
mechanical under the beta formula, while the relationship to rare-class performance is
|
||||
confounded by which classes are rare and how much support they have in each partition.
|
||||
|
||||
---
|
||||
|
||||
## I. Relation to RQ2 (how beta changes prototypes and rare-class performance)
|
||||
|
||||
- **Prototype position:** increasing beta moves every class prototype monotonically away from
|
||||
its beta=0 equal mean (by construction, because supports are unequal); the magnitude grows
|
||||
with support imbalance (mean class displacement at beta=1: 1.31 / 2.10 / 3.42 as imbalance
|
||||
grows). `|S_j| = 1` would leave the aggregate unchanged, but that case does not occur here.
|
||||
- **Rare-class performance:** the validation response is **non-monotone in beta** and
|
||||
condition-dependent: monotone decreasing at alpha=0.25, peaking at 0.75 at alpha=0.50,
|
||||
peaking at 0.50 at alpha=0.75. The effect magnitude is small relative to between-seed
|
||||
variance at all three conditions.
|
||||
|
||||
---
|
||||
|
||||
## J. Relation to RQ3 (does selected beta differ across non-IID conditions?)
|
||||
|
||||
Yes, descriptively: the pooled-selected beta is **0.00 (alpha=0.25), 0.75 (alpha=0.50),
|
||||
0.50 (alpha=0.75)**. It is **not monotone** in alpha.
|
||||
|
||||
Caveats that forbid a trend claim:
|
||||
|
||||
- only **three** alpha levels and **three** project-defined seeds, **one** dataset;
|
||||
- one selection per condition, each statistically weak (between-seed std ≈ between-beta
|
||||
spread or larger) and with **no tie-break** exercised;
|
||||
- the realized partitions differ, so the non-IID "condition" is only partially summarized by
|
||||
alpha;
|
||||
- **no inferential monotonic-trend test** has been performed.
|
||||
|
||||
RQ3 asks whether beta changes with conditions; it does not require a monotonic answer.
|
||||
|
||||
---
|
||||
|
||||
## K. Limitations
|
||||
|
||||
- One dataset (X-IIoTID), three alpha values, three seeds; no cross-dataset claim.
|
||||
- The `S_j` participant/denominator rule remains a **REPRODUCTION ASSUMPTION** (material in
|
||||
19/27 cells at alpha=0.25, 7/27 at alpha=0.50, 3/27 at alpha=0.75); all comparisons are
|
||||
conditional on both modes sharing it.
|
||||
- Train/validation/test adaptation (70/10/20 stratified) differs from the paper's literal
|
||||
80/20; the validation eval partition is a project decision.
|
||||
- **No 5G-NIDD beta result yet.**
|
||||
- **No inferential significance testing**; no global beta optimum. Each selected beta is
|
||||
"best among the tested candidates under pooled validation for that condition".
|
||||
- Cross-alpha absolute metrics are not directly comparable because the rare-class sets, global
|
||||
rare support, and per-client eval partitions differ by condition/seed; only within-condition
|
||||
contrasts and relative patterns are interpreted.
|
||||
@@ -0,0 +1,230 @@
|
||||
#!/usr/bin/env python
|
||||
"""Read-only cross-alpha comparison for the X-IIoTID beta study.
|
||||
|
||||
Aggregates the audited per-condition multiseed artifacts of several Dirichlet
|
||||
alpha levels into a single machine-readable comparison:
|
||||
|
||||
- ``*__cross_alpha_beta_table.csv`` — alpha x beta pooled validation mean/std,
|
||||
pooled recall, selected flag, and the realized heterogeneity summary fields;
|
||||
- ``*__cross_alpha_displacement.csv`` — per-class direct prototype displacement
|
||||
``||Cbar_j(beta)-Cbar_j(0)||`` by alpha;
|
||||
- ``*__cross_alpha_client_summary.csv`` — client improve/degrade/unchanged counts
|
||||
by alpha/seed/beta;
|
||||
- ``*__cross_alpha_summary.json`` — condition-level pooled selections and ranges.
|
||||
|
||||
Reads only existing analysis artifacts; no training, no test-based selection.
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import argparse
|
||||
import csv
|
||||
import json
|
||||
import sys
|
||||
from pathlib import Path
|
||||
|
||||
REPO_ROOT = Path(__file__).resolve().parents[1]
|
||||
sys.path.insert(0, str(REPO_ROOT / "src"))
|
||||
|
||||
from protean_research.aggregation import BETA_CANDIDATES # noqa: E402
|
||||
|
||||
|
||||
def read_csv(path: Path) -> list[dict]:
|
||||
with path.open("r", encoding="utf-8", newline="") as handle:
|
||||
return list(csv.DictReader(handle))
|
||||
|
||||
|
||||
def read_json(path: Path):
|
||||
with path.open("r", encoding="utf-8") as handle:
|
||||
return json.load(handle)
|
||||
|
||||
|
||||
def write_csv(path: Path, rows: list[dict]) -> None:
|
||||
path.parent.mkdir(parents=True, exist_ok=True)
|
||||
if not rows:
|
||||
path.write_text("", encoding="utf-8")
|
||||
return
|
||||
with path.open("w", encoding="utf-8", newline="") as handle:
|
||||
writer = csv.DictWriter(handle, fieldnames=list(rows[0].keys()))
|
||||
writer.writeheader()
|
||||
writer.writerows(rows)
|
||||
|
||||
|
||||
def parse_args(argv=None) -> argparse.Namespace:
|
||||
parser = argparse.ArgumentParser(description=__doc__)
|
||||
parser.add_argument("--dataset", default="xiiotid")
|
||||
parser.add_argument("--alphas", type=float, nargs="+", default=[0.25, 0.5, 0.75])
|
||||
parser.add_argument("--seeds", type=int, nargs="+", default=[0, 1, 2])
|
||||
parser.add_argument("--analysis-dir", default="artifacts/analysis")
|
||||
parser.add_argument("--tag", default=None)
|
||||
return parser.parse_args(argv)
|
||||
|
||||
|
||||
def _resolve(path: str) -> Path:
|
||||
p = Path(path).expanduser()
|
||||
return p if p.is_absolute() else REPO_ROOT / p
|
||||
|
||||
|
||||
def main(argv=None) -> int:
|
||||
args = parse_args(argv)
|
||||
analysis = _resolve(args.analysis_dir)
|
||||
tag = args.tag or f"{args.dataset}__cross_alpha"
|
||||
|
||||
het_tag = f"{args.dataset}__cross_alpha__partition_heterogeneity"
|
||||
het_summary = {
|
||||
float(row["alpha"]): row
|
||||
for row in read_csv(analysis / f"{het_tag}_summary.csv")
|
||||
}
|
||||
|
||||
beta_table: list[dict] = []
|
||||
displacement_rows: list[dict] = []
|
||||
client_rows: list[dict] = []
|
||||
summary = {"dataset": args.dataset, "alphas": {}, "betas": list(BETA_CANDIDATES)}
|
||||
|
||||
for alpha in args.alphas:
|
||||
stem = f"{args.dataset}__alpha{alpha:g}__multiseed"
|
||||
pooled_path = analysis / f"{stem}__validation_pooled.csv"
|
||||
selection_path = analysis / f"{stem}__selection_summary.json"
|
||||
effect_path = analysis / f"{stem}__prototype_effect_pooled.csv"
|
||||
client_path = analysis / f"{stem}__client_validation_summary.csv"
|
||||
test_path = analysis / f"{stem}__test_descriptive.csv"
|
||||
|
||||
pooled = read_csv(pooled_path)
|
||||
selection = read_json(selection_path)
|
||||
selected_beta = selection["primary_selection"]["selected_beta"]
|
||||
het = het_summary.get(float(alpha), {})
|
||||
|
||||
effect = read_csv(effect_path) if effect_path.exists() else []
|
||||
for row in effect:
|
||||
displacement_rows.append({
|
||||
"dataset": args.dataset,
|
||||
"alpha": alpha,
|
||||
"class_id": int(row["class_id"]),
|
||||
"class_name": row["class_name"],
|
||||
"beta": float(row["beta"]),
|
||||
"n_seeds": int(row["n_seeds"]),
|
||||
"mean_displacement": float(row["mean_displacement"]),
|
||||
"std_sample_displacement": (
|
||||
float(row["std_sample_displacement"])
|
||||
if row["std_sample_displacement"] not in ("", "None")
|
||||
else None
|
||||
),
|
||||
"mean_relative_displacement": (
|
||||
float(row["mean_relative_displacement"])
|
||||
if row["mean_relative_displacement"] not in ("", "None")
|
||||
else None
|
||||
),
|
||||
})
|
||||
|
||||
if client_path.exists():
|
||||
for row in read_csv(client_path):
|
||||
client_rows.append({
|
||||
"dataset": args.dataset,
|
||||
"alpha": alpha,
|
||||
"seed": int(row["seed"]),
|
||||
"beta": float(row["beta"]),
|
||||
"n_eligible": int(row["n_eligible"]),
|
||||
"n_improve": int(row["n_improve_vs_beta0"]),
|
||||
"n_degrade": int(row["n_degrade_vs_beta0"]),
|
||||
"n_unchanged": int(row["n_unchanged"]),
|
||||
"mean_delta": (
|
||||
float(row["mean_delta_vs_beta0"])
|
||||
if row["mean_delta_vs_beta0"] not in ("", "None")
|
||||
else None
|
||||
),
|
||||
"min_delta": (
|
||||
float(row["min_delta_vs_beta0"])
|
||||
if row["min_delta_vs_beta0"] not in ("", "None")
|
||||
else None
|
||||
),
|
||||
"max_delta": (
|
||||
float(row["max_delta_vs_beta0"])
|
||||
if row["max_delta_vs_beta0"] not in ("", "None")
|
||||
else None
|
||||
),
|
||||
})
|
||||
|
||||
disp_beta1 = [
|
||||
r for r in displacement_rows
|
||||
if r["alpha"] == alpha and abs(r["beta"] - 1.0) <= 1e-9
|
||||
]
|
||||
mean_disp_beta1 = (
|
||||
sum(r["mean_displacement"] for r in disp_beta1) / len(disp_beta1)
|
||||
if disp_beta1 else None
|
||||
)
|
||||
|
||||
for row in pooled:
|
||||
beta = float(row["beta"])
|
||||
beta_table.append({
|
||||
"dataset": args.dataset,
|
||||
"alpha": alpha,
|
||||
"beta": beta,
|
||||
"n_seeds": int(row["n_seeds"]),
|
||||
"pooled_val_mean": float(
|
||||
row["pooled_val_rare_macro_f1_per_client_mean"]
|
||||
),
|
||||
"pooled_val_std_sample": float(row["std_sample_val_rare_macro_f1"]),
|
||||
"pooled_val_std_pop": float(row["std_pop_val_rare_macro_f1"]),
|
||||
"pooled_val_min": float(row["min_val_rare_macro_f1"]),
|
||||
"pooled_val_max": float(row["max_val_rare_macro_f1"]),
|
||||
"pooled_val_recall": float(
|
||||
row["pooled_val_rare_recall_per_client_mean"]
|
||||
),
|
||||
"selected": abs(beta - selected_beta) <= 1e-12,
|
||||
"cells_sj_lt_M_total": int(het.get("cells_sj_lt_M_total", -1)),
|
||||
"cells_total": int(het.get("cells_total", -1)),
|
||||
"missing_client_class_cells_total": int(
|
||||
het.get("missing_client_class_cells_total", -1)
|
||||
),
|
||||
"client_size_ratio_mean": float(het.get("client_size_ratio_mean", -1)),
|
||||
"support_cv_mean": float(het.get("support_cv_mean", -1)),
|
||||
"union_unseen_mean": float(het.get("union_unseen_mean", -1)),
|
||||
"mean_displacement_beta1": mean_disp_beta1,
|
||||
})
|
||||
|
||||
summary["alphas"][f"{alpha:g}"] = {
|
||||
"selected_beta": selected_beta,
|
||||
"tie_break_used": selection["primary_selection"]["tie_break_used"],
|
||||
"selection_rule": selection["primary_selection"]["rule"],
|
||||
"test_used_for_selection": selection["primary_selection"][
|
||||
"test_used_for_selection"
|
||||
],
|
||||
"pooled_val_mean_range": [
|
||||
min(float(r["pooled_val_mean"]) for r in beta_table
|
||||
if r["alpha"] == alpha),
|
||||
max(float(r["pooled_val_mean"]) for r in beta_table
|
||||
if r["alpha"] == alpha),
|
||||
],
|
||||
"pooled_val_std_sample_range": [
|
||||
min(float(r["pooled_val_std_sample"]) for r in beta_table
|
||||
if r["alpha"] == alpha),
|
||||
max(float(r["pooled_val_std_sample"]) for r in beta_table
|
||||
if r["alpha"] == alpha),
|
||||
],
|
||||
"cells_sj_lt_M_total": int(het.get("cells_sj_lt_M_total", -1)),
|
||||
"cells_total": int(het.get("cells_total", -1)),
|
||||
"missing_client_class_cells_total": int(
|
||||
het.get("missing_client_class_cells_total", -1)
|
||||
),
|
||||
"client_size_ratio_mean": float(het.get("client_size_ratio_mean", -1)),
|
||||
"support_cv_mean": float(het.get("support_cv_mean", -1)),
|
||||
"union_unseen_mean": float(het.get("union_unseen_mean", -1)),
|
||||
"mean_displacement_beta1": mean_disp_beta1,
|
||||
"test_descriptive_present": test_path.exists(),
|
||||
}
|
||||
|
||||
write_csv(analysis / f"{tag}__cross_alpha_beta_table.csv", beta_table)
|
||||
write_csv(analysis / f"{tag}__cross_alpha_displacement.csv", displacement_rows)
|
||||
write_csv(analysis / f"{tag}__cross_alpha_client_summary.csv", client_rows)
|
||||
with (analysis / f"{tag}__cross_alpha_summary.json").open(
|
||||
"w", encoding="utf-8"
|
||||
) as handle:
|
||||
json.dump(summary, handle, indent=2, sort_keys=True)
|
||||
handle.write("\n")
|
||||
|
||||
print(json.dumps(summary, indent=2, sort_keys=True))
|
||||
return 0
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
raise SystemExit(main())
|
||||
@@ -0,0 +1,213 @@
|
||||
#!/usr/bin/env python
|
||||
"""Read-only realized non-IID characterization from persisted partition manifests.
|
||||
|
||||
For each ``(dataset, alpha, seed)`` manifest this script reconstructs the training
|
||||
class-support matrix ``N_ij`` and emits machine-readable heterogeneity statistics:
|
||||
|
||||
- ``*__partition_heterogeneity_per_class.csv`` — one row per ``(alpha, seed, class)``
|
||||
with the protocol-required ``min/max/mean/std/CV/max-min`` inequality measures;
|
||||
- ``*__partition_heterogeneity_per_seed.csv`` — one row per ``(alpha, seed)`` with
|
||||
``|S_j| < M`` cell count, missing client-class cells, client-size spread,
|
||||
rare/unseen counts and class-CV summaries;
|
||||
- ``*__partition_heterogeneity_summary.csv`` — per-alpha aggregation across seeds.
|
||||
|
||||
This reads existing manifests only. It never regenerates a partition, never reads
|
||||
test data and never trains.
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import argparse
|
||||
import csv
|
||||
import json
|
||||
import statistics
|
||||
import sys
|
||||
from pathlib import Path
|
||||
|
||||
REPO_ROOT = Path(__file__).resolve().parents[1]
|
||||
sys.path.insert(0, str(REPO_ROOT / "src"))
|
||||
|
||||
from protean_research.data import manifest as manifest_mod # noqa: E402
|
||||
from protean_research.data.characterization import characterize_support # noqa: E402
|
||||
from protean_research.data.rare_unseen import ( # noqa: E402
|
||||
rare_class_ids_for_client,
|
||||
unseen_class_ids_for_client,
|
||||
)
|
||||
|
||||
|
||||
def write_csv(path: Path, rows: list[dict]) -> None:
|
||||
path.parent.mkdir(parents=True, exist_ok=True)
|
||||
if not rows:
|
||||
path.write_text("", encoding="utf-8")
|
||||
return
|
||||
with path.open("w", encoding="utf-8", newline="") as handle:
|
||||
writer = csv.DictWriter(handle, fieldnames=list(rows[0].keys()))
|
||||
writer.writeheader()
|
||||
writer.writerows(rows)
|
||||
|
||||
|
||||
def parse_args(argv=None) -> argparse.Namespace:
|
||||
parser = argparse.ArgumentParser(description=__doc__)
|
||||
parser.add_argument("--dataset", default="xiiotid")
|
||||
parser.add_argument("--alphas", type=float, nargs="+", default=[0.75, 0.5, 0.25])
|
||||
parser.add_argument("--seeds", type=int, nargs="+", default=[0, 1, 2])
|
||||
parser.add_argument("--partitions-dir", default="artifacts/partitions")
|
||||
parser.add_argument("--analysis-dir", default="artifacts/analysis")
|
||||
parser.add_argument(
|
||||
"--tag", default=None,
|
||||
help="output stem (default: <dataset>__cross_alpha__partition_heterogeneity)",
|
||||
)
|
||||
return parser.parse_args(argv)
|
||||
|
||||
|
||||
def _resolve(path: str) -> Path:
|
||||
p = Path(path).expanduser()
|
||||
return p if p.is_absolute() else REPO_ROOT / p
|
||||
|
||||
|
||||
def main(argv=None) -> int:
|
||||
import numpy as np
|
||||
|
||||
args = parse_args(argv)
|
||||
partitions_dir = _resolve(args.partitions_dir)
|
||||
analysis_dir = _resolve(args.analysis_dir)
|
||||
tag = args.tag or f"{args.dataset}__cross_alpha__partition_heterogeneity"
|
||||
|
||||
per_class_rows: list[dict] = []
|
||||
per_seed_rows: list[dict] = []
|
||||
|
||||
for alpha in args.alphas:
|
||||
for seed in args.seeds:
|
||||
path = manifest_mod.manifest_path(partitions_dir, args.dataset, alpha, seed)
|
||||
manifest = manifest_mod.load_manifest(path)
|
||||
support = np.asarray(manifest["support"], dtype=np.int64)
|
||||
class_names = list(manifest["class_names"])
|
||||
benign_index = class_names.index(manifest["benign_class"])
|
||||
num_clients = int(manifest["num_clients"])
|
||||
num_classes = int(manifest["num_classes"])
|
||||
assert support.shape == (num_clients, num_classes)
|
||||
|
||||
class_stats = characterize_support(support, class_names)
|
||||
for row in class_stats:
|
||||
per_class_rows.append({
|
||||
"dataset": args.dataset,
|
||||
"alpha": alpha,
|
||||
"seed": seed,
|
||||
**row,
|
||||
})
|
||||
|
||||
sj = (support > 0).sum(axis=0)
|
||||
cells_lt_m = int((sj < num_clients).sum())
|
||||
missing_cells = int((support == 0).sum())
|
||||
|
||||
totals = support.sum(axis=1).astype(int)
|
||||
client_min = int(totals.min())
|
||||
client_max = int(totals.max())
|
||||
client_ratio = float(client_max / client_min) if client_min > 0 else None
|
||||
|
||||
rare_lists = [
|
||||
rare_class_ids_for_client(support[c], benign_index)
|
||||
for c in range(num_clients)
|
||||
]
|
||||
unseen_lists = [
|
||||
unseen_class_ids_for_client(support[c], benign_index)
|
||||
for c in range(num_clients)
|
||||
]
|
||||
union_rare = sorted({c for row in rare_lists for c in row})
|
||||
union_unseen = sorted({c for row in unseen_lists for c in row})
|
||||
|
||||
cvs = [row["cv"] for row in class_stats if row["total"] > 0]
|
||||
max_min_values = [
|
||||
row["max_min_ratio"] for row in class_stats if row["max_min_ratio"] > 0
|
||||
]
|
||||
|
||||
per_seed_rows.append({
|
||||
"dataset": args.dataset,
|
||||
"alpha": alpha,
|
||||
"seed": seed,
|
||||
"num_clients": num_clients,
|
||||
"num_classes": num_classes,
|
||||
"num_train": int(manifest["num_train"]),
|
||||
"nij_sum": int(support.sum()),
|
||||
"n_class_condition_cells": num_classes,
|
||||
"n_cells_sj_lt_M": cells_lt_m,
|
||||
"n_missing_client_class_cells": missing_cells,
|
||||
"client_size_min": client_min,
|
||||
"client_size_max": client_max,
|
||||
"client_size_ratio": client_ratio,
|
||||
"union_rare_count": len(union_rare),
|
||||
"union_unseen_count": len(union_unseen),
|
||||
"max_unseen_on_client": max((len(u) for u in unseen_lists), default=0),
|
||||
"n_clients_2_rare": sum(1 for r in rare_lists if len(r) == 2),
|
||||
"support_cv_mean": statistics.fmean(cvs) if cvs else None,
|
||||
"support_cv_max": max(cvs) if cvs else None,
|
||||
"support_max_min_ratio_max": max(max_min_values) if max_min_values else None,
|
||||
"manifest_content_hash": manifest_mod.manifest_content_hash(manifest),
|
||||
"partition_hash": manifest["partition_hash"],
|
||||
"split_hash": manifest["split"]["hash"],
|
||||
"rng_seed": int(manifest["rng_seed"]),
|
||||
})
|
||||
|
||||
# per-alpha summary across seeds
|
||||
summary_rows: list[dict] = []
|
||||
for alpha in args.alphas:
|
||||
subset = [r for r in per_seed_rows if r["alpha"] == alpha]
|
||||
if not subset:
|
||||
continue
|
||||
summary_rows.append({
|
||||
"dataset": args.dataset,
|
||||
"alpha": alpha,
|
||||
"n_seeds": len(subset),
|
||||
"cells_sj_lt_M_total": sum(r["n_cells_sj_lt_M"] for r in subset),
|
||||
"cells_total": sum(r["n_class_condition_cells"] for r in subset),
|
||||
"missing_client_class_cells_total": sum(
|
||||
r["n_missing_client_class_cells"] for r in subset
|
||||
),
|
||||
"client_size_ratio_mean": statistics.fmean(
|
||||
r["client_size_ratio"] for r in subset
|
||||
),
|
||||
"client_size_ratio_max": max(r["client_size_ratio"] for r in subset),
|
||||
"union_unseen_mean": statistics.fmean(r["union_unseen_count"] for r in subset),
|
||||
"max_unseen_on_client": max(r["max_unseen_on_client"] for r in subset),
|
||||
"union_rare_mean": statistics.fmean(r["union_rare_count"] for r in subset),
|
||||
"support_cv_mean": statistics.fmean(r["support_cv_mean"] for r in subset),
|
||||
"support_max_min_ratio_max": max(
|
||||
r["support_max_min_ratio_max"] for r in subset
|
||||
),
|
||||
})
|
||||
|
||||
write_csv(analysis_dir / f"{tag}_per_class.csv", per_class_rows)
|
||||
write_csv(analysis_dir / f"{tag}_per_seed.csv", per_seed_rows)
|
||||
write_csv(analysis_dir / f"{tag}_summary.csv", summary_rows)
|
||||
|
||||
payload = {
|
||||
"dataset": args.dataset,
|
||||
"alphas": args.alphas,
|
||||
"seeds": args.seeds,
|
||||
"per_class": str(analysis_dir / f"{tag}_per_class.csv"),
|
||||
"per_seed": str(analysis_dir / f"{tag}_per_seed.csv"),
|
||||
"summary": str(analysis_dir / f"{tag}_summary.csv"),
|
||||
"per_seed_rows": per_seed_rows,
|
||||
"summary_rows": summary_rows,
|
||||
}
|
||||
out_json = analysis_dir / f"{tag}.json"
|
||||
with out_json.open("w", encoding="utf-8") as handle:
|
||||
json.dump(payload, handle, indent=2, sort_keys=True)
|
||||
handle.write("\n")
|
||||
|
||||
print(json.dumps({
|
||||
"tag": tag,
|
||||
"n_per_class_rows": len(per_class_rows),
|
||||
"n_per_seed_rows": len(per_seed_rows),
|
||||
"summary": [{"alpha": r["alpha"],
|
||||
"cells_sj_lt_M": f"{r['cells_sj_lt_M_total']}/{r['cells_total']}",
|
||||
"missing_cells": r["missing_client_class_cells_total"],
|
||||
"client_ratio_mean": round(r["client_size_ratio_mean"], 3)}
|
||||
for r in summary_rows],
|
||||
"json": str(out_json),
|
||||
}, indent=2))
|
||||
return 0
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
raise SystemExit(main())
|
||||
@@ -0,0 +1,209 @@
|
||||
#!/usr/bin/env python
|
||||
"""Read-only ``beta = 0`` vs ``original_protean`` equivalence audit.
|
||||
|
||||
For each seed of one ``(dataset, alpha)`` condition this compares the frozen
|
||||
``original_protean`` run with the ``support_weighted beta=0`` run:
|
||||
|
||||
- manifest content hash, round-0 snapshot bytes, support/characterization/
|
||||
rare-unseen artifact bytes (pairing / identity);
|
||||
- independent aggregation arithmetic on the shared round-0 snapshot
|
||||
(``original_protean`` equal mean vs ``support_weighted beta=0``);
|
||||
- downstream divergence (history and test-metric numeric deltas).
|
||||
|
||||
Classification per seed:
|
||||
A — semantic + numerical identity;
|
||||
B — semantic equivalence + floating-point divergence;
|
||||
C — semantic discrepancy.
|
||||
|
||||
Read-only: no training, no aggregation source change.
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import argparse
|
||||
import csv
|
||||
import hashlib
|
||||
import json
|
||||
import sys
|
||||
from pathlib import Path
|
||||
|
||||
REPO_ROOT = Path(__file__).resolve().parents[1]
|
||||
sys.path.insert(0, str(REPO_ROOT / "src"))
|
||||
|
||||
from protean_research.aggregation import ( # noqa: E402
|
||||
AggregationMode,
|
||||
aggregate_class_prototypes,
|
||||
)
|
||||
from protean_research.analysis.direct_prototype import ( # noqa: E402
|
||||
snapshot_contributions,
|
||||
)
|
||||
|
||||
PAIR_FILES = ("train_support_Nij.csv", "characterization.csv", "rare_unseen.csv")
|
||||
|
||||
|
||||
def sha256_bytes(path: Path) -> str:
|
||||
return hashlib.sha256(path.read_bytes()).hexdigest()
|
||||
|
||||
|
||||
def read_json(path: Path):
|
||||
with path.open("r", encoding="utf-8") as handle:
|
||||
return json.load(handle)
|
||||
|
||||
|
||||
def numeric_max_abs_diff(a, b) -> float:
|
||||
if isinstance(a, dict) and isinstance(b, dict):
|
||||
diffs = [
|
||||
numeric_max_abs_diff(a[k], b[k])
|
||||
for k in a.keys() & b.keys()
|
||||
if isinstance(a[k], (int, float)) and isinstance(b[k], (int, float))
|
||||
]
|
||||
return max(diffs) if diffs else 0.0
|
||||
if isinstance(a, list) and isinstance(b, list) and len(a) == len(b):
|
||||
diffs = [numeric_max_abs_diff(x, y) for x, y in zip(a, b)]
|
||||
return max(diffs) if diffs else 0.0
|
||||
if isinstance(a, (int, float)) and isinstance(b, (int, float)):
|
||||
return abs(float(a) - float(b))
|
||||
return 0.0
|
||||
|
||||
|
||||
def history_rare_f1(history) -> list[float]:
|
||||
return [
|
||||
float(row["rare_class_macro_f1"])
|
||||
for row in history
|
||||
if row.get("rare_class_macro_f1") is not None
|
||||
]
|
||||
|
||||
|
||||
def max_abs_diff(xs, ys) -> float:
|
||||
return max((abs(x - y) for x, y in zip(xs, ys)), default=0.0)
|
||||
|
||||
|
||||
def aggregation_difference(snapshot) -> float:
|
||||
contributions = snapshot_contributions(snapshot)
|
||||
original = aggregate_class_prototypes(
|
||||
contributions, AggregationMode.ORIGINAL_PROTEAN
|
||||
)
|
||||
beta0 = aggregate_class_prototypes(
|
||||
contributions, AggregationMode.SUPPORT_WEIGHTED, beta=0.0
|
||||
)
|
||||
diffs = []
|
||||
for class_id in original:
|
||||
diffs.extend(abs(x - y) for x, y in zip(original[class_id], beta0[class_id]))
|
||||
return max(diffs) if diffs else 0.0
|
||||
|
||||
|
||||
def parse_args(argv=None) -> argparse.Namespace:
|
||||
parser = argparse.ArgumentParser(description=__doc__)
|
||||
parser.add_argument("--dataset", required=True)
|
||||
parser.add_argument("--alpha", type=float, required=True)
|
||||
parser.add_argument("--seeds", type=int, nargs="+", default=[0, 1, 2])
|
||||
parser.add_argument("--results-dir", default="results")
|
||||
parser.add_argument("--analysis-dir", default="artifacts/analysis")
|
||||
parser.add_argument("--tag", default=None)
|
||||
return parser.parse_args(argv)
|
||||
|
||||
|
||||
def _resolve(path: str) -> Path:
|
||||
p = Path(path).expanduser()
|
||||
return p if p.is_absolute() else REPO_ROOT / p
|
||||
|
||||
|
||||
def main(argv=None) -> int:
|
||||
args = parse_args(argv)
|
||||
results = _resolve(args.results_dir)
|
||||
analysis = _resolve(args.analysis_dir)
|
||||
tag = args.tag or f"{args.dataset}__alpha{args.alpha:g}__multiseed"
|
||||
|
||||
rows: list[dict] = []
|
||||
for seed in args.seeds:
|
||||
orig_name = f"{args.dataset}__alpha{args.alpha:g}__seed{seed}__original_protean"
|
||||
b0_name = (
|
||||
f"{args.dataset}__alpha{args.alpha:g}__seed{seed}"
|
||||
"__support_weighted__beta0"
|
||||
)
|
||||
orig_dir = results / orig_name
|
||||
b0_dir = results / b0_name
|
||||
|
||||
orig_meta = read_json(orig_dir / "metadata.json")
|
||||
b0_meta = read_json(b0_dir / "metadata.json")
|
||||
|
||||
orig_snap = analysis / f"{orig_name}__prototype_snapshot.json"
|
||||
b0_snap = analysis / f"{b0_name}__prototype_snapshot.json"
|
||||
orig_snap_hash = sha256_bytes(orig_snap) if orig_snap.exists() else None
|
||||
b0_snap_hash = sha256_bytes(b0_snap) if b0_snap.exists() else None
|
||||
|
||||
pair_hashes = {}
|
||||
pair_identical = True
|
||||
for filename in PAIR_FILES:
|
||||
o = orig_dir / filename
|
||||
b = b0_dir / filename
|
||||
same = o.exists() and b.exists() and sha256_bytes(o) == sha256_bytes(b)
|
||||
pair_hashes[filename] = same
|
||||
pair_identical = pair_identical and same
|
||||
|
||||
history_orig = read_json(orig_dir / "history.json")
|
||||
history_b0 = read_json(b0_dir / "history.json")
|
||||
f1_orig = history_rare_f1(history_orig)
|
||||
f1_b0 = history_rare_f1(history_b0)
|
||||
round0_diff = max_abs_diff(f1_orig[:1], f1_b0[:1])
|
||||
later_diff = max_abs_diff(f1_orig[1:], f1_b0[1:])
|
||||
|
||||
test_diff = numeric_max_abs_diff(
|
||||
read_json(orig_dir / "test_global_metrics.json"),
|
||||
read_json(b0_dir / "test_global_metrics.json"),
|
||||
)
|
||||
|
||||
agg_diff = aggregation_difference(read_json(b0_snap))
|
||||
|
||||
same_manifest = (
|
||||
orig_meta.get("manifest_content_hash") == b0_meta.get("manifest_content_hash")
|
||||
)
|
||||
semantic_ok = (
|
||||
same_manifest
|
||||
and orig_snap_hash is not None
|
||||
and orig_snap_hash == b0_snap_hash
|
||||
and pair_identical
|
||||
and agg_diff <= 1e-12
|
||||
)
|
||||
numerical_identity = (
|
||||
semantic_ok
|
||||
and later_diff == 0.0
|
||||
and test_diff == 0.0
|
||||
and history_orig == history_b0
|
||||
)
|
||||
if numerical_identity:
|
||||
classification = "A"
|
||||
elif semantic_ok:
|
||||
classification = "B"
|
||||
else:
|
||||
classification = "C"
|
||||
|
||||
rows.append({
|
||||
"dataset": args.dataset,
|
||||
"alpha": args.alpha,
|
||||
"seed": seed,
|
||||
"same_manifest_content_hash": same_manifest,
|
||||
"round0_snapshot_sha256_original": orig_snap_hash,
|
||||
"round0_snapshot_sha256_beta0": b0_snap_hash,
|
||||
"round0_snapshot_byte_identical": orig_snap_hash == b0_snap_hash,
|
||||
"support_char_rare_identical": pair_identical,
|
||||
"aggregation_max_abs_diff": agg_diff,
|
||||
"history_rare_f1_round0_diff": round0_diff,
|
||||
"history_rare_f1_max_diff_rounds_ge1": later_diff,
|
||||
"test_metric_max_abs_diff": test_diff,
|
||||
"classification": classification,
|
||||
})
|
||||
|
||||
out = analysis / f"{tag}__beta0_equivalence.csv"
|
||||
out.parent.mkdir(parents=True, exist_ok=True)
|
||||
with out.open("w", encoding="utf-8", newline="") as handle:
|
||||
writer = csv.DictWriter(handle, fieldnames=list(rows[0].keys()))
|
||||
writer.writeheader()
|
||||
writer.writerows(rows)
|
||||
|
||||
print(json.dumps({"output": str(out), "rows": rows}, indent=2, default=str))
|
||||
return 0
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
raise SystemExit(main())
|
||||
Reference in new issue
Block a user