{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006740644,0.001214523,0.0009064582,0.002030492,0.0005022846,0.001427445,0.001036961,0.001372581,0.001406841],"category_scores_gemma":[0.01174211,0.000191745,0.0008213436,0.0008800455,0.0004882151,0.001604103,0.0009678925,0.0004724782,0.0008516966],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001172416,"about_ca_system_score_gemma":0.0008716356,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005705306,"about_ca_topic_score_gemma":0.004507937,"domain_scores_codex":[0.9939367,0.002193607,0.0008686776,0.0008595739,0.001846415,0.0002951279],"domain_scores_gemma":[0.9926853,0.003024163,0.0006974282,0.0009690914,0.002351201,0.0002727328],"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":[0.00752775,0.004096775,0.1441583,0.001770694,0.001473926,0.0005850629,0.0004526917,0.1774514,0.04704009,0.004107587,0.01074905,0.6005867],"study_design_scores_gemma":[0.0001228273,0.003417945,0.04345507,0.00009361852,0.000167205,0.000447102,0.0003235078,0.9111489,0.03819481,0.0005625351,0.002012659,0.00005390002],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9444484,0.0008707708,0.04542373,0.0003095318,0.0002187497,0.0005883789,0.001659095,0.002933586,0.003547641],"genre_scores_gemma":[0.9705528,0.0002124227,0.02443909,0.00005627015,0.0000204232,0.0001204673,0.003356287,0.00002250772,0.00121965],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006740644,"threshold_uncertainty_score":0.03564835,"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."}}