{"id":"W4292002652","doi":"10.1109/csr54599.2022.9850286","title":"A Stable Generative Adversarial Network Architecture for Network Intrusion Detection","year":2022,"lang":"en","type":"article","venue":"","topic":"Network Security and Intrusion Detection","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Computer science; Discriminative model; Convolutional neural network; Artificial intelligence; Machine learning; Intrusion detection system; Sensitivity (control systems); Process (computing); Data mining; Generative grammar; Pattern recognition (psychology); Anomaly detection; Task (project management); Engineering","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001422765,0.001067979,0.0008349713,0.0006857566,0.0003038838,0.0006058565,0.001397584,0.0008492979,0.001279715],"category_scores_gemma":[0.002284016,0.0004545652,0.0009232295,0.0004910809,0.0008164693,0.0009629151,0.001225034,0.00203547,0.0005190324],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008904868,"about_ca_system_score_gemma":0.0005714875,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00371356,"about_ca_topic_score_gemma":0.003826661,"domain_scores_codex":[0.9993629,0.0002045274,0.00002605114,0.0001705351,0.0001576112,0.00007837582],"domain_scores_gemma":[0.9991973,0.0003629409,0.00008779101,0.0001158676,0.0001973296,0.00003874236],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00008645522,0.00004374161,0.00126077,0.00003202198,0.00008113858,0.0000728982,0.00004810655,0.8963512,0.004005325,0.007932435,0.001809378,0.08827653],"study_design_scores_gemma":[0.000001070109,0.00001008813,0.00007106345,0.000001940403,0.000004850838,0.00001333773,0.000001220063,0.9980828,0.0004992741,0.0011477,0.0001638958,0.000002805665],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01903553,0.0005431778,0.9765204,0.0003215958,0.00007219179,0.00004231748,0.00008459432,0.001315737,0.002064356],"genre_scores_gemma":[0.8413045,0.0006094807,0.1508684,0.0004229612,0.00008976724,0.0001262645,0.0004762088,0.0001451685,0.005957347],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00371356,"threshold_uncertainty_score":0.007524371,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01057834041349465,"score_gpt":0.2159367403245715,"score_spread":0.2053583999110768,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}