{"id":"W4241500940","doi":"10.32920/ryerson.14656188","title":"Continuous Authentication Based On Learning User Command Sequence","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Network Security and Intrusion Detection","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Computer science; Intrusion detection system; Sequence (biology); Classifier (UML); Naive Bayes classifier; Authentication (law); Data mining; Artificial intelligence; Context (archaeology); Machine learning; Computer security; Support vector machine","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":[0.002133649,0.0007785981,0.001145309,0.001704631,0.0005611572,0.001017941,0.001060134,0.0008091577,0.0009002168],"category_scores_gemma":[0.007945094,0.0002326132,0.00053784,0.0008778124,0.000744484,0.001992914,0.0008341824,0.001128434,0.0009345877],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008095737,"about_ca_system_score_gemma":0.001246998,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003335106,"about_ca_topic_score_gemma":0.002853323,"domain_scores_codex":[0.9978555,0.0005637353,0.0001714629,0.0005185773,0.0007039524,0.0001868345],"domain_scores_gemma":[0.9939188,0.002357074,0.0007901428,0.0009828086,0.001572861,0.0003782254],"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":[0.002419825,0.0008895934,0.0566171,0.0002154469,0.0001373596,0.000353895,0.0004462108,0.1059832,0.04006299,0.005480686,0.004498072,0.7828957],"study_design_scores_gemma":[0.00001924318,0.0002530796,0.003330466,0.000009963503,0.00002034133,0.000173482,0.00004124833,0.9806589,0.01233071,0.002518784,0.0006219418,0.0000218878],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3027288,0.000470996,0.69022,0.0002717954,0.0001419789,0.0002655446,0.000245398,0.003776506,0.001879022],"genre_scores_gemma":[0.9276517,0.00010656,0.07041923,0.00005988266,0.00004317956,0.0000586005,0.0003464363,0.00002567396,0.00128879],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003335106,"threshold_uncertainty_score":0.01128399,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0242483778035423,"score_gpt":0.2577603609228192,"score_spread":0.2335119831192769,"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."}}