{"id":"W4302602562","doi":"10.1145/3538969.3543788","title":"SAMM: Situation Awareness with Machine Learning for Misbehavior Detection in VANET","year":2022,"lang":"en","type":"article","venue":"Proceedings of the 17th International Conference on Availability, Reliability and Security","topic":"Vehicular Ad Hoc Networks (VANETs)","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"Computer science; Vehicular ad hoc network; Artificial intelligence; Machine learning; Telecommunications; Wireless ad hoc network; Wireless","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":[0.001005379,0.000178276,0.0002240665,0.00008252454,0.0001818683,0.00005142208,0.0003191452,0.0000728663,0.00009590423],"category_scores_gemma":[0.00033607,0.0001546929,0.00006649877,0.0002218092,0.0001115729,0.0001782207,0.0001732284,0.0005963667,8.094485e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003092527,"about_ca_system_score_gemma":0.00005040116,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001197568,"about_ca_topic_score_gemma":0.0005216044,"domain_scores_codex":[0.9985667,0.00004396533,0.0003598584,0.0003882541,0.0004390975,0.0002021639],"domain_scores_gemma":[0.999172,0.0001199553,0.0001288963,0.0001334326,0.0003966622,0.0000490692],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001694213,0.0009336903,0.5739033,0.001148441,0.00009751154,0.000001618894,0.003435062,0.3876587,0.01547694,0.008595366,0.0001661862,0.006889021],"study_design_scores_gemma":[0.0009084859,0.000294572,0.03336847,0.00006589187,0.00003019589,0.00001649715,0.0003888076,0.9391785,0.009579343,0.0147854,0.001142834,0.0002409761],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9973448,0.00003327795,0.0001381024,0.0004952046,0.0002848512,0.0006289655,0.00006759249,0.00007711232,0.0009301025],"genre_scores_gemma":[0.9994547,0.00003274648,0.0001402458,0.00002580493,0.00002964345,0.0002076976,0.0000276665,0.00001840569,0.00006313854],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5515198,"threshold_uncertainty_score":0.6308192,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0171058685024525,"score_gpt":0.2379335088711036,"score_spread":0.2208276403686511,"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."}}