{"id":"W2124689666","doi":"10.3233/jcs-2010-0412","title":"Leveraging personal devices for stronger password authentication from untrusted computers","year":2011,"lang":"en","type":"article","venue":"Journal of Computer Security","topic":"User Authentication and Security Systems","field":"Computer Science","cited_by":42,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University; University of Toronto","funders":"","keywords":"Password; Computer science; Computer security; Authentication (law); Email authentication; One-time password; Phishing; Usability; Chip Authentication Program; Database transaction; Personally identifiable information; Mobile device; Multi-factor authentication; The Internet; Internet privacy; World Wide Web; Authentication protocol; Database; Human–computer interaction","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":[0.00157807,0.0008590787,0.0006757035,0.001103735,0.0009115731,0.002370683,0.00180469,0.001652124,0.007564072],"category_scores_gemma":[0.006740592,0.0006453715,0.0008053255,0.0009936269,0.001152335,0.007782565,0.004914111,0.002025167,0.006372637],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002864059,"about_ca_system_score_gemma":0.0003798948,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001792803,"about_ca_topic_score_gemma":0.0003325935,"domain_scores_codex":[0.9967341,0.0009689714,0.0003625201,0.0004335995,0.001194234,0.0003065645],"domain_scores_gemma":[0.9900102,0.001874565,0.0009631799,0.005708149,0.001128038,0.0003158939],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001586891,0.0005846796,0.01298657,0.002063661,0.0003019502,0.002792686,0.001839302,0.00485284,0.1855083,0.1220514,0.01894149,0.6464903],"study_design_scores_gemma":[0.0004809668,0.004343953,0.02013132,0.001529329,0.0008257106,0.01974375,0.001027637,0.1488215,0.3262043,0.0810565,0.3952552,0.0005799464],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1748566,0.008022761,0.741231,0.002939848,0.001215617,0.0007185218,0.0002255274,0.005972356,0.06481787],"genre_scores_gemma":[0.8497034,0.002959856,0.1273839,0.0009894361,0.0006689428,0.0002182045,0.0002426302,0.0001700406,0.01766353],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007564072,"threshold_uncertainty_score":0.02530432,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04019401013647549,"score_gpt":0.2474682426283154,"score_spread":0.2072742324918399,"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."}}