{"id":"W4388565318","doi":"10.1007/s11227-023-05764-5","title":"ICS-IDS: application of big data analysis in AI-based intrusion detection systems to identify cyberattacks in ICS networks","year":2023,"lang":"en","type":"article","venue":"The Journal of Supercomputing","topic":"Network Security and Intrusion Detection","field":"Computer Science","cited_by":64,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université de Moncton","funders":"","keywords":"Computer science; Intrusion detection system; Data mining; Component (thermodynamics); Industrial control system; Artificial intelligence; Machine learning; Normalization (sociology); Curse of dimensionality; Control (management)","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":[0.005932076,0.0001281282,0.0003617636,0.001268654,0.0001439575,0.0001257112,0.001216618,0.0001072794,0.000001044203],"category_scores_gemma":[0.00008894195,0.0001038694,0.00008233204,0.006743835,0.00002656721,0.0005014188,0.000531576,0.0005303229,0.00000464545],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000128172,"about_ca_system_score_gemma":0.00005333006,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008529919,"about_ca_topic_score_gemma":0.001125657,"domain_scores_codex":[0.9974986,0.0005037183,0.001010457,0.0002589784,0.000463155,0.000265121],"domain_scores_gemma":[0.9983146,0.0004333707,0.0003797274,0.0005994494,0.0002062016,0.00006669301],"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":[0.00003461098,0.00003667424,0.004603089,0.00001779061,0.00003213799,0.000005518888,0.0006303829,0.8830893,0.004051,0.00003188448,0.00005742309,0.1074102],"study_design_scores_gemma":[0.0002649282,0.00008104349,0.01758395,0.0001550067,0.00004327334,0.00001647656,0.0002006665,0.9805353,0.0008074324,0.0001160019,0.00009706903,0.00009887307],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4405906,0.0001106689,0.5583785,0.0002240384,0.0005537547,0.0001175735,8.036745e-7,0.00001975374,0.000004286591],"genre_scores_gemma":[0.9987369,0.00006787748,0.0006581463,0.0001100225,0.0004083746,0.000001986698,0.000006516116,0.000008837585,0.00000137153],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5581462,"threshold_uncertainty_score":0.4235671,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03874495637911218,"score_gpt":0.3072545786417354,"score_spread":0.2685096222626232,"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."}}