{"id":"W4210827399","doi":"10.1109/tits.2022.3147354","title":"Efficient and Anonymous Authentication With Succinct Multi-Subscription Credential in SAGVN","year":2022,"lang":"en","type":"article","venue":"IEEE Transactions on Intelligent Transportation Systems","topic":"Advanced Authentication Protocols Security","field":"Computer Science","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University; McMaster University; University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Credential; Computer science; Authentication (law); Computer security; Computer network; Anonymity; Service (business); Key (lock); Message authentication code; Cryptography","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003981234,0.0005145611,0.001075605,0.001021941,0.001297735,0.002057516,0.002196894,0.001321176,0.001309472],"category_scores_gemma":[0.006853375,0.0003831869,0.0007649266,0.001134074,0.001803317,0.005520815,0.004983161,0.001738241,0.0006505242],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001244808,"about_ca_system_score_gemma":0.002381938,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001047319,"about_ca_topic_score_gemma":0.0007592201,"domain_scores_codex":[0.9936753,0.002197486,0.0006495464,0.0006984743,0.002037053,0.0007421774],"domain_scores_gemma":[0.9940889,0.001553953,0.000677844,0.002313233,0.0009562843,0.0004097706],"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":[0.00161917,0.000440507,0.003454756,0.0004283037,0.0001455919,0.001373551,0.001360673,0.107041,0.05568528,0.6338081,0.003583166,0.1910599],"study_design_scores_gemma":[0.000146989,0.0003944249,0.0007250048,0.00007155957,0.00009242717,0.001297999,0.0002828639,0.8052484,0.03534068,0.1379851,0.01823129,0.0001832599],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03526393,0.0002120093,0.9602676,0.0002230543,0.0001043831,0.0002267083,0.00005953368,0.0007685411,0.002874146],"genre_scores_gemma":[0.9027568,0.000180011,0.09356987,0.0001846551,0.00005843785,0.0001691113,0.000163601,0.00003778432,0.002879801],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003981234,"threshold_uncertainty_score":0.02105504,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02250147420654046,"score_gpt":0.2596782982087575,"score_spread":0.2371768240022171,"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."}}