{"id":"W3014071235","doi":"10.1002/nem.2109","title":"Exploring anomalous behaviour detection and classification for insider threat identification","year":2020,"lang":"en","type":"article","venue":"International Journal of Network Management","topic":"Network Security and Intrusion Detection","field":"Computer Science","cited_by":55,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"","keywords":"Insider threat; Computer science; Anomaly detection; Identification (biology); Insider; Context (archaeology); Machine learning; Artificial intelligence; Adaptation (eye); Granularity; Computer security; Data mining","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003775722,0.00009217527,0.0001097943,0.0001260308,0.0001046142,0.000244488,0.0004432383,0.00002998794,0.000004052228],"category_scores_gemma":[0.0000250214,0.00009213034,0.00007632926,0.0001986804,0.00001626952,0.001151759,0.0001396218,0.0001114214,0.000005268887],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007365143,"about_ca_system_score_gemma":0.000008549985,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001978377,"about_ca_topic_score_gemma":0.000003702603,"domain_scores_codex":[0.9988242,0.00004019288,0.0004492115,0.0002061442,0.0003587706,0.000121424],"domain_scores_gemma":[0.999056,0.00004559028,0.0004044589,0.0001103374,0.0003066991,0.00007688573],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002517928,0.00008166351,0.001172834,0.00003168405,0.0002574275,0.00003768819,0.0008771645,0.005673303,0.001336474,0.03774638,0.00185904,0.9506745],"study_design_scores_gemma":[0.003250868,0.001105793,0.2338155,0.0002476723,0.0002025326,0.0002674714,0.0004988406,0.6474494,0.003120713,0.0285003,0.08090859,0.0006323709],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.100179,0.0001730346,0.893297,0.003666979,0.002262354,0.0002136494,8.301859e-7,0.00004173364,0.000165392],"genre_scores_gemma":[0.9878072,0.0007487989,0.009821751,0.0004573824,0.001105175,0.00002840555,0.000001974339,0.00000800102,0.00002128316],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9500422,"threshold_uncertainty_score":0.3756967,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09171610357745036,"score_gpt":0.2734909576613411,"score_spread":0.1817748540838907,"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."}}