{"id":"W3013184273","doi":"10.1145/3372420","title":"Mimicry Attacks on Smartphone Keystroke Authentication","year":2020,"lang":"en","type":"article","venue":"ACM Transactions on Privacy and Security","topic":"User Authentication and Security Systems","field":"Computer Science","cited_by":23,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo; University of Guelph","funders":"Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada","keywords":"Keystroke logging; Computer science; Password; Keystroke dynamics; Authentication (law); Computer security; Human–computer interaction; S/KEY","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0001766559,0.0001893032,0.0002001749,0.0000996708,0.0002938159,0.0001781891,0.0008965152,0.0001033184,0.00006465637],"category_scores_gemma":[0.00007214243,0.000184006,0.0001003523,0.0003333724,0.00005681993,0.0003670206,0.0000357733,0.0003248826,0.0002255052],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002755348,"about_ca_system_score_gemma":0.00003464341,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001427139,"about_ca_topic_score_gemma":0.000004997209,"domain_scores_codex":[0.9984845,0.0001291842,0.0003058953,0.0005507051,0.0002982674,0.0002314624],"domain_scores_gemma":[0.9985198,0.0001512803,0.00008145126,0.0009328213,0.00005866709,0.0002559381],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0005369869,0.003838355,0.001491091,0.0006814203,0.0005152181,0.00004850416,0.7019342,0.00006833899,0.01218019,0.1149423,0.006312764,0.1574506],"study_design_scores_gemma":[0.009714936,0.003434488,0.02947345,0.000412199,0.0002961663,0.0001440275,0.002118743,0.4862487,0.08314764,0.1000629,0.2813949,0.003551838],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4546297,0.0001005406,0.4935162,0.04953395,0.0005220349,0.0005100218,0.0000380844,0.0005129219,0.0006364743],"genre_scores_gemma":[0.9956785,0.00007543318,0.001383992,0.002668835,0.00004886009,0.00002843659,0.000006640033,0.00001126264,0.0000980093],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6998155,"threshold_uncertainty_score":0.7503546,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03201625026099603,"score_gpt":0.255703336578352,"score_spread":0.223687086317356,"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."}}