{"id":"W3114527962","doi":"10.1109/isncc49221.2020.9297252","title":"Designing Security User Profiles via Anomaly Detection for User Authentication","year":2020,"lang":"en","type":"article","venue":"","topic":"Advanced Malware Detection Techniques","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"","keywords":"Computer science; Anomaly detection; Authentication (law); 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":[0.0001512422,0.000121286,0.0001109898,0.0000688265,0.0001481379,0.00009819288,0.0003528275,0.00007181249,0.00001428706],"category_scores_gemma":[0.0001135586,0.000118853,0.00006271958,0.0003405167,0.00002025168,0.0009010152,0.000107519,0.00009334247,0.00002591238],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000450731,"about_ca_system_score_gemma":0.00002033493,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001048151,"about_ca_topic_score_gemma":0.000008777719,"domain_scores_codex":[0.9990052,0.00003957631,0.0002031431,0.0004179189,0.0001421757,0.000191976],"domain_scores_gemma":[0.9993096,0.00007341471,0.0001015196,0.0002729486,0.0001554534,0.00008704165],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00006271251,0.00007277039,0.0003950882,0.0001054348,0.00002823426,0.000002362324,0.001709003,0.00008115603,0.8871205,0.0232624,0.001089741,0.08607056],"study_design_scores_gemma":[0.0001371515,0.0001939953,0.0002066062,0.000004350495,0.00000528729,0.000004326558,0.00002293436,0.08910568,0.8953656,0.009296567,0.005503016,0.0001544702],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.005029356,0.00001026878,0.9915964,0.000770268,0.0001119692,0.0006561495,0.000001337713,0.001697338,0.000126908],"genre_scores_gemma":[0.6118035,0.000001122719,0.3875405,0.0003491649,0.00005323873,0.000157523,0.000001198242,0.00001013452,0.00008362625],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.6067742,"threshold_uncertainty_score":0.4846684,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01819559784895303,"score_gpt":0.2568333151657557,"score_spread":0.2386377173168027,"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."}}