{"id":"W2148675241","doi":"10.1109/iaw.2005.1495997","title":"Anomaly intrusion detection based on biometrics","year":2005,"lang":"en","type":"article","venue":"","topic":"User Authentication and Security Systems","field":"Computer Science","cited_by":106,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"","keywords":"Keystroke dynamics; Biometrics; Computer science; Profiling (computer programming); Intrusion detection system; Anomaly detection; Intrusion; Forcing (mathematics); Data mining; Artificial intelligence; Computer security; Operating system; Password","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":[0.000203287,0.00005759587,0.00005449025,0.0004353304,0.00006883679,0.0001120572,0.000296484,0.00003837705,0.00005004262],"category_scores_gemma":[0.00003338273,0.0000480536,0.00003171399,0.001033475,0.000007382453,0.0001941251,0.00003502085,0.00004475114,0.0005745612],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004586458,"about_ca_system_score_gemma":0.00001450383,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000017299,"about_ca_topic_score_gemma":0.00002513371,"domain_scores_codex":[0.999321,0.00003592845,0.00012828,0.0001878458,0.0002225833,0.0001043466],"domain_scores_gemma":[0.9994595,0.00004738842,0.00003587505,0.0003546272,0.00004508372,0.00005750376],"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":[0.00001118433,0.0004737174,0.001238378,0.00001741962,0.000007707931,0.00000235897,0.003728268,0.0001185899,0.00907667,0.02545651,0.001480959,0.9583882],"study_design_scores_gemma":[0.0001617301,0.00006274432,0.002466314,0.000003079961,8.069227e-7,0.000001518234,0.000005090848,0.9440357,0.01700728,0.00008501371,0.03610033,0.00007038104],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06422968,0.00001075622,0.9268029,0.002322323,0.000301748,0.0000978564,3.109423e-7,0.0002689708,0.005965416],"genre_scores_gemma":[0.9929518,9.665363e-7,0.00537831,0.001120293,0.00005604372,0.000004197377,6.790418e-7,0.000002962572,0.000484778],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9583179,"threshold_uncertainty_score":0.7385014,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01461557351344593,"score_gpt":0.235161952578015,"score_spread":0.2205463790645691,"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."}}