{"id":"W2092919558","doi":"10.1016/j.cose.2012.02.005","title":"Systematically breaking and fixing OpenID security: Formal analysis, semi-automated empirical evaluation, and practical countermeasures","year":2012,"lang":"en","type":"article","venue":"Computers & Security","topic":"Web Application Security Vulnerabilities","field":"Computer Science","cited_by":49,"is_retracted":false,"has_abstract":false,"ca_institutions":"Dalhousie University; University of British Columbia","funders":"","keywords":"Computer science; Single sign-on; Computer security; Protocol (science); Password; Security analysis; Authentication (law); Scalability; World Wide Web; Database","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":[0.02531378,0.001108146,0.0006593227,0.004211637,0.001367446,0.003199793,0.002729148,0.001757032,0.002051264],"category_scores_gemma":[0.1917072,0.0008741187,0.001157069,0.001591125,0.004063828,0.006491387,0.003780439,0.003309836,0.0003267889],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003310923,"about_ca_system_score_gemma":0.007067241,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003787237,"about_ca_topic_score_gemma":0.007073143,"domain_scores_codex":[0.9668998,0.01635436,0.002486215,0.00248841,0.0102461,0.001525071],"domain_scores_gemma":[0.6910973,0.2242345,0.0199024,0.04097277,0.02230745,0.001485625],"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":[0.001580568,0.003794339,0.1369206,0.002376357,0.0004771838,0.0005058926,0.008255824,0.1645199,0.04375733,0.09366325,0.004641269,0.5395074],"study_design_scores_gemma":[0.000408303,0.00189118,0.02723657,0.0007345793,0.0003283837,0.0005081515,0.00425152,0.7892078,0.061079,0.1083745,0.005732326,0.0002476783],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6723439,0.0004055313,0.3172048,0.001343476,0.00007965198,0.0008658465,0.0004072213,0.002887253,0.004462339],"genre_scores_gemma":[0.8709213,0.0001193567,0.1277827,0.000101539,0.0000121384,0.0002594086,0.0003047456,0.0001205769,0.0003781161],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02531378,"threshold_uncertainty_score":0.1338736,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03740046871827278,"score_gpt":0.3539438400005536,"score_spread":0.3165433712822808,"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."}}