{"id":"W4229627031","doi":"10.1109/infocom.2007.58","title":"An Efficient Identity-Based Batch Verification Scheme for Vehicular Sensor Networks","year":2008,"lang":"en","type":"article","venue":"2008 Proceedings IEEE INFOCOM - The 27th Conference on Computer Communications","topic":"Advanced Authentication Protocols Security","field":"Computer Science","cited_by":74,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Computer network; Scalability; Overhead (engineering); Authentication (law); Scheme (mathematics); Wireless sensor network; Tamper resistance; Transmission (telecommunications); Digital signature; Dedicated short-range communications; Computer security; Wireless; Hash function; Telecommunications","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":[0.001958221,0.0006074101,0.0009553222,0.0005290028,0.001126434,0.001132805,0.002535263,0.0008802485,0.001534681],"category_scores_gemma":[0.00366409,0.0003387326,0.0005426006,0.0007994621,0.0008825711,0.002864542,0.002142805,0.001283361,0.0007251042],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00135898,"about_ca_system_score_gemma":0.002469942,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001897725,"about_ca_topic_score_gemma":0.00138274,"domain_scores_codex":[0.997543,0.000530807,0.0002354731,0.0004897923,0.0009005166,0.0003004125],"domain_scores_gemma":[0.9976079,0.0004900091,0.0003466738,0.0008895355,0.0005251003,0.0001408],"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":[0.002937586,0.0002888957,0.001797167,0.0003831899,0.0001224382,0.0006961327,0.0006659966,0.1667266,0.1797034,0.2804669,0.009285078,0.3569266],"study_design_scores_gemma":[0.000150825,0.00043623,0.0003809083,0.00002094372,0.00005228149,0.0003806337,0.0000603816,0.9051923,0.05211521,0.02972902,0.01138423,0.0000971096],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02216095,0.0003023825,0.9739702,0.0001793446,0.0001365195,0.0001719831,0.0001189268,0.0009209108,0.002038755],"genre_scores_gemma":[0.7806017,0.0002552893,0.2131464,0.0001203128,0.0001032986,0.0002277542,0.0004378962,0.00004461404,0.005062767],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.002535263,"threshold_uncertainty_score":0.01035619,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0722334421260509,"score_gpt":0.3237108225046818,"score_spread":0.2514773803786309,"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."}}