{"id":"W4317207036","doi":"10.3390/app13031252","title":"Explainable Artificial Intelligence (XAI) for Intrusion Detection and Mitigation in Intelligent Connected Vehicles: A Review","year":2023,"lang":"en","type":"review","venue":"Applied Sciences","topic":"Adversarial Robustness in Machine Learning","field":"Computer Science","cited_by":173,"is_retracted":false,"has_abstract":true,"ca_institutions":"Conestoga College","funders":"Institute for Information and Communications Technology Promotion; Ministry of Science and ICT, South Korea; Ministry of Education, Science and Technology; National Research Foundation of Korea; National Research Foundation","keywords":"Computer science; Transparency (behavior); Computer security; Scope (computer science); Intrusion detection system; Internet of Things","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.003260934,0.0003564192,0.0009708838,0.0005303922,0.0004811909,0.0002821801,0.001177586,0.0002021702,0.00000577975],"category_scores_gemma":[0.000871764,0.0003027572,0.0001271277,0.002846842,0.0002625552,0.0002884183,0.0005292968,0.0004185364,0.00004872852],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001606388,"about_ca_system_score_gemma":0.0002562799,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003112162,"about_ca_topic_score_gemma":0.00008388454,"domain_scores_codex":[0.9968473,0.0002140932,0.0009414903,0.001105404,0.0004233042,0.0004684514],"domain_scores_gemma":[0.9976005,0.001352307,0.0005373961,0.0003581025,0.00006757701,0.00008413976],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000001945869,0.00001116335,2.551006e-7,0.00873032,0.000006595203,0.00000216335,0.000153284,0.0002480013,0.000005122551,0.0428987,0.00001110005,0.9479313],"study_design_scores_gemma":[0.0002448382,0.0006002032,0.000005890858,0.1323621,0.0004450429,0.00008113662,0.001225877,0.2915567,0.0005112738,0.1918905,0.3781115,0.002964871],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.000007942452,0.5917506,0.4057474,0.0001013985,0.0003418393,0.001783606,0.000001756567,0.0001562813,0.0001092128],"genre_scores_gemma":[0.0004289907,0.9861623,0.01235806,0.00008309285,0.0001145843,0.0007985582,0.00001025275,0.00002420368,0.00001993534],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9449665,"threshold_uncertainty_score":0.9999425,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1006367250751149,"score_gpt":0.3679713352342253,"score_spread":0.2673346101591104,"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."}}