{"id":"W4405113743","doi":"10.1016/j.procs.2024.11.109","title":"Intrusion Detection in IIoT Using Machine Learning","year":2024,"lang":"en","type":"article","venue":"Procedia Computer Science","topic":"Network Security and Intrusion Detection","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Rimouski; Cégep de Rimouski","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Intrusion detection system; Artificial intelligence; Machine learning; Data mining","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":[0.002019374,0.001132209,0.001217512,0.002715908,0.0005050513,0.001361685,0.0009561536,0.001007364,0.0003488629],"category_scores_gemma":[0.003498629,0.0002243381,0.0009148734,0.001459908,0.0005204096,0.001561561,0.001175768,0.0009651203,0.0003547474],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007442275,"about_ca_system_score_gemma":0.0005781447,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003379396,"about_ca_topic_score_gemma":0.004174163,"domain_scores_codex":[0.9981498,0.0004387128,0.0001955665,0.0004286697,0.0005833342,0.0002039509],"domain_scores_gemma":[0.9977967,0.000983445,0.0003566322,0.0003569697,0.0004124577,0.00009386696],"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":[0.001772805,0.00141521,0.1067667,0.0006567953,0.0004819699,0.00123451,0.0002904285,0.3075063,0.02744925,0.003322698,0.01489359,0.5342098],"study_design_scores_gemma":[0.00002436089,0.0002590656,0.01071059,0.00003477944,0.00004276036,0.0003996527,0.0001160584,0.9654061,0.0168907,0.0027884,0.003303622,0.00002375902],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7873023,0.002330928,0.193488,0.0008831086,0.0003341782,0.0003989889,0.004256343,0.007102061,0.003903988],"genre_scores_gemma":[0.9218602,0.0003962782,0.06811427,0.0001418703,0.00006719818,0.0001260538,0.007982656,0.00006803478,0.001243478],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003379396,"threshold_uncertainty_score":0.0106796,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01393506185490988,"score_gpt":0.2450794846223368,"score_spread":0.2311444227674269,"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."}}