{"id":"W4400577032","doi":"10.5220/0012792800003767","title":"Enhancing Adversarial Defense in Behavioral Authentication Systems Through Random Projections","year":2024,"lang":"en","type":"article","venue":"","topic":"User Authentication and Security Systems","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"Concordia University of Edmonton","funders":"","keywords":"Adversarial system; Computer science; Authentication (law); Computer security; Artificial intelligence","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":[0.002750342,0.001033234,0.0009627679,0.0005285461,0.0007782216,0.00125919,0.001131365,0.001303996,0.002944269],"category_scores_gemma":[0.01153312,0.0005028481,0.0005320787,0.0004373513,0.001730182,0.003114108,0.003622286,0.002566184,0.001083841],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000585063,"about_ca_system_score_gemma":0.0009756883,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003952231,"about_ca_topic_score_gemma":0.0005207083,"domain_scores_codex":[0.9957893,0.002085668,0.0001200258,0.0004567848,0.001029245,0.0005189584],"domain_scores_gemma":[0.9916368,0.004608325,0.0005967259,0.002007467,0.0008066182,0.0003440573],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001218976,0.0005419858,0.002026591,0.0001697745,0.0001504317,0.0003154592,0.0003460443,0.559507,0.05202245,0.2668323,0.003850396,0.1130186],"study_design_scores_gemma":[0.00001722175,0.0001252696,0.0001804689,0.000008654108,0.00001327198,0.00009611366,0.0000217005,0.9566295,0.005812152,0.03662781,0.0004513779,0.00001647835],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04965239,0.000114615,0.9444411,0.000526062,0.00007082405,0.0000747683,0.0000413288,0.0009640438,0.004114878],"genre_scores_gemma":[0.9564184,0.00008458766,0.04049413,0.0001361083,0.0000497771,0.00005193394,0.00003932004,0.00004653526,0.002679186],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002944269,"threshold_uncertainty_score":0.01454532,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03028852012344179,"score_gpt":0.3038794362259902,"score_spread":0.2735909161025484,"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."}}