{"id":"W3136769223","doi":"10.1016/j.ijcip.2021.100430","title":"ARTINALI#: An Efficient Intrusion Detection Technique for Resource-Constrained Cyber-Physical Systems","year":2021,"lang":"en","type":"article","venue":"International Journal of Critical Infrastructure Protection","topic":"Network Security and Intrusion Detection","field":"Computer Science","cited_by":17,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Intrusion detection system; Computer science; Overhead (engineering); Cyber-physical system; Set (abstract data type); Distributed computing; Embedded system; Resource (disambiguation); Software deployment; Real-time computing; Computer security; Computer network; Operating system","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":[0.0004828787,0.00106484,0.0006089094,0.001225063,0.0006164425,0.0008409339,0.001460311,0.0005339531,0.00439731],"category_scores_gemma":[0.001219039,0.0003735833,0.0004988415,0.0005937588,0.0004745045,0.001640075,0.00106646,0.000886284,0.001257472],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000479884,"about_ca_system_score_gemma":0.0008022762,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001534428,"about_ca_topic_score_gemma":0.004640006,"domain_scores_codex":[0.999427,0.00008300027,0.00003032703,0.00008861138,0.0003196686,0.00005146522],"domain_scores_gemma":[0.999514,0.0001377206,0.00005415188,0.0001272799,0.0001332327,0.00003367768],"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":[0.0007621306,0.0001432356,0.001807608,0.0003464159,0.0001546199,0.0004280136,0.0001630444,0.02485332,0.1165291,0.01355935,0.03846786,0.8027852],"study_design_scores_gemma":[0.00008398086,0.0003495847,0.001388686,0.0000397847,0.0000770862,0.0008704985,0.00004988606,0.8252321,0.1141687,0.009924131,0.04774299,0.00007241287],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02573603,0.001099357,0.9256839,0.000404199,0.0004799735,0.0001263016,0.0003644547,0.03609195,0.01001393],"genre_scores_gemma":[0.2707124,0.0004781343,0.7072156,0.0004796533,0.0001497454,0.0001176882,0.0007283689,0.001143846,0.01897452],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00439731,"threshold_uncertainty_score":0.01471043,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01174774818974608,"score_gpt":0.2819583278569864,"score_spread":0.2702105796672403,"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."}}