{"id":"W2107397689","doi":"10.1109/compsac.2010.70","title":"PAAKL: Password Authentication Using Behavioral Metrics","year":2010,"lang":"en","type":"article","venue":"","topic":"User Authentication and Security Systems","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"","keywords":"Password; Computer science; S/KEY; Cognitive password; Password policy; Password strength; Computer security; One-time password; Correctness; Salt (chemistry); Authentication (law); Programming language","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":[0.0003003032,0.00008452612,0.00009110465,0.0001791778,0.0001063821,0.0002630982,0.000644525,0.00007129672,0.00008036027],"category_scores_gemma":[0.00003081962,0.0000756959,0.00005104045,0.0006148213,0.0000270029,0.000414319,0.0001126736,0.00013951,0.0001620872],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001693381,"about_ca_system_score_gemma":0.00004269436,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001088754,"about_ca_topic_score_gemma":0.00005603205,"domain_scores_codex":[0.9990455,0.00003466309,0.0002162998,0.0002492747,0.0002767889,0.0001774559],"domain_scores_gemma":[0.9990159,0.00003169,0.00007504564,0.0006539064,0.0001182438,0.0001051875],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000002248037,0.0007342296,0.02417029,0.00002309338,0.00002394914,0.000007154635,0.0303879,0.000001118718,0.1338641,0.7702163,0.001167897,0.03940172],"study_design_scores_gemma":[0.0003355085,0.0000395836,0.0105222,0.000006458135,0.0000247419,0.00004155087,0.0001317669,0.9476504,0.009856916,0.005688659,0.02531542,0.0003867987],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6377587,0.000008577992,0.3593301,0.0005201192,0.001117262,0.0001348389,8.260751e-7,0.0002447609,0.0008848346],"genre_scores_gemma":[0.9684343,6.196255e-7,0.0307415,0.00009153106,0.00005212264,0.000005726456,0.000001981708,0.000006224315,0.0006660378],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9476493,"threshold_uncertainty_score":0.3086789,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04743501799862428,"score_gpt":0.3178993209722848,"score_spread":0.2704643029736606,"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."}}