{"id":"W3081807059","doi":"10.1186/s13673-020-00241-x","title":"SD2PA: a fully safe driving and privacy-preserving authentication scheme for VANETs","year":2020,"lang":"en","type":"article","venue":"Human-centric Computing and Information Sciences","topic":"Vehicular Ad Hoc Networks (VANETs)","field":"Engineering","cited_by":34,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Windsor","funders":"","keywords":"Vehicular ad hoc network; Computer science; Anonymity; Authentication (law); Computer security; Scheme (mathematics); Hash function; Redundancy (engineering); Overhead (engineering); Computer network; Message authentication code; Wireless ad hoc network; Cryptography; Wireless; Telecommunications","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":[0.0004986819,0.0001263814,0.0001443599,0.0001198515,0.0005165675,0.0004016511,0.0002288008,0.00004610083,0.00001287227],"category_scores_gemma":[0.0001989734,0.0001229735,0.00002666627,0.0003760491,0.0000718247,0.001256738,0.0001744246,0.0001023063,0.000008566701],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002372382,"about_ca_system_score_gemma":0.0000193652,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004323007,"about_ca_topic_score_gemma":0.000001351602,"domain_scores_codex":[0.9989321,0.00001683299,0.0003616742,0.0001595164,0.0002273947,0.0003025014],"domain_scores_gemma":[0.9994854,0.0001165369,0.0001085287,0.00009893247,0.00006299341,0.0001275828],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000008694057,0.00001763674,0.008060153,0.0007955959,0.00005118601,9.981328e-7,0.0163941,0.8580895,0.001046845,0.00817997,0.006615103,0.1007402],"study_design_scores_gemma":[0.0003130334,0.00004071493,0.005018117,0.00005729086,0.000008195486,0.000006071342,0.0002580475,0.9818649,0.00005813963,0.0001091308,0.01211788,0.0001484318],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8841473,0.0004358395,0.1129354,0.000455656,0.0001349436,0.0003385277,0.000002092301,0.0002445416,0.001305675],"genre_scores_gemma":[0.9929146,0.00004924217,0.006708186,0.0001833822,0.000113553,0.000004467096,0.00001464033,0.000006289273,0.000005688147],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1237755,"threshold_uncertainty_score":0.5014716,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02247011894819622,"score_gpt":0.2549975156515963,"score_spread":0.2325273967034001,"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."}}