{"id":"W4399728995","doi":"10.1109/syscon61195.2024.10553463","title":"Anomaly Detection and Functional Testing for Automotive CAN Communication","year":2024,"lang":"en","type":"article","venue":"","topic":"Vehicular Ad Hoc Networks (VANETs)","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ontario Tech University","funders":"","keywords":"Anomaly detection; Automotive industry; Computer science; Artificial intelligence; Engineering","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":[0.00116787,0.0007403423,0.0004848033,0.001889244,0.0004186454,0.000594966,0.001242765,0.0007594646,0.0009805901],"category_scores_gemma":[0.007542596,0.0001713097,0.0004352883,0.000813107,0.0009324356,0.001181301,0.0008477043,0.0009079843,0.0002322247],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009704479,"about_ca_system_score_gemma":0.001079599,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003790374,"about_ca_topic_score_gemma":0.002913875,"domain_scores_codex":[0.9986506,0.0003247031,0.00006761836,0.0002501756,0.0005530572,0.0001538047],"domain_scores_gemma":[0.9967883,0.001609147,0.0005677656,0.000322454,0.0005835514,0.000128873],"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":[0.0005912986,0.0004119737,0.05747439,0.0002145388,0.0001324894,0.0007682331,0.0003582566,0.5081531,0.02962038,0.01633919,0.00252855,0.3834075],"study_design_scores_gemma":[0.000005389842,0.00007486256,0.002116109,0.000006237527,0.000006965934,0.00009936262,0.00002647991,0.9886913,0.004710976,0.003907946,0.0003471233,0.000007364175],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2652132,0.0003845486,0.7273939,0.0005950464,0.00007843624,0.00009813876,0.0001870472,0.003962987,0.002086609],"genre_scores_gemma":[0.9653274,0.00005912588,0.03386258,0.00005230555,0.00002128615,0.00003701386,0.0001303519,0.00003900345,0.0004710351],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003790374,"threshold_uncertainty_score":0.00753665,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01565891569519964,"score_gpt":0.2076414990241914,"score_spread":0.1919825833289918,"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."}}