{"id":"W4280539069","doi":"10.5539/cis.v15n3p1","title":"Evaluation of a User Authentication Schema Using Behavioral Biometrics and Machine Learning","year":2022,"lang":"en","type":"article","venue":"Computer and Information Science","topic":"User Authentication and Security Systems","field":"Computer Science","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"University of Wisconsin-Eau Claire","keywords":"Computer science; Biometrics; Password; Support vector machine; Artificial intelligence; Random forest; Machine learning; Naive Bayes classifier; Modal; Authentication (law); Behavioral pattern; Data mining; Computer security","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003605516,0.00006278813,0.0000849043,0.0007751145,0.0004883224,0.0002904292,0.0003670874,0.00001454017,0.000009125035],"category_scores_gemma":[0.00005779082,0.00006256832,0.0000151657,0.001828289,0.0001188785,0.004115638,0.0005386359,0.00008020415,0.000001878977],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000733538,"about_ca_system_score_gemma":0.0001476695,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002514609,"about_ca_topic_score_gemma":3.390589e-7,"domain_scores_codex":[0.9981574,0.0001104799,0.0002945223,0.000157267,0.001164157,0.0001161817],"domain_scores_gemma":[0.998966,0.00002583626,0.0002142154,0.0001986651,0.0005315893,0.00006365694],"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":[0.000009300663,0.000266,0.01932153,0.0001188256,0.00002363864,4.082225e-7,0.2179086,0.003349636,0.008863968,0.09454018,0.00005574733,0.6555421],"study_design_scores_gemma":[0.0002607618,0.00006678521,0.01030478,0.000004966398,0.00001081518,0.00001845528,0.0001617748,0.9871184,0.0003176141,0.0001580955,0.001505164,0.00007238838],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6816192,0.0000676565,0.3177616,0.00006952018,0.0002287691,0.0001611141,0.000002409977,0.0000290504,0.00006058321],"genre_scores_gemma":[0.9928031,0.000005421144,0.007116528,0.00004915851,0.000007017108,0.000008470106,0.00000493917,0.000001409467,0.000003975339],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9837688,"threshold_uncertainty_score":0.3755831,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0868236142221541,"score_gpt":0.3245638630602245,"score_spread":0.2377402488380704,"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."}}