{"id":"W3013585180","doi":"10.1109/ccnc46108.2020.9045195","title":"Encoded Flow Features for Network Intrusion Detection in Internet of Things","year":2020,"lang":"en","type":"article","venue":"","topic":"Network Security and Intrusion Detection","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"Intrusion detection system; Computer science; Leverage (statistics); Discriminative model; Support vector machine; The Internet; Internet of Things; Artificial intelligence; Machine learning; Codebook; Variety (cybernetics); Data mining; Computer security; World Wide Web","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":[0.0004495284,0.0005040889,0.0004822065,0.001797748,0.0002132502,0.0004290434,0.000420621,0.0004235457,0.0007594759],"category_scores_gemma":[0.002719257,0.0001304816,0.0003408614,0.001150447,0.000236051,0.001058781,0.0004286994,0.0005263594,0.0002456548],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003462818,"about_ca_system_score_gemma":0.0003032638,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001835453,"about_ca_topic_score_gemma":0.001597125,"domain_scores_codex":[0.9996762,0.00004987445,0.00002690083,0.00005469316,0.000156048,0.0000362568],"domain_scores_gemma":[0.9992041,0.000331666,0.0001261106,0.00009054127,0.0002168034,0.00003073656],"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":[0.0005259615,0.0004302408,0.01302092,0.000178576,0.00007610478,0.0003671712,0.00008596753,0.12875,0.04091608,0.006524439,0.007488639,0.8016359],"study_design_scores_gemma":[0.00001894981,0.0001662089,0.007662097,0.00002675243,0.00003086856,0.0003171687,0.00003646475,0.9673804,0.01566071,0.005567122,0.003103185,0.00003005797],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2311221,0.001511833,0.7592022,0.0004404655,0.0002905231,0.0001897785,0.001344257,0.003177224,0.002721573],"genre_scores_gemma":[0.8811524,0.0004812743,0.114827,0.0001058212,0.00009769478,0.0001008815,0.002075173,0.00005270489,0.001106992],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001835453,"threshold_uncertainty_score":0.003649592,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01235013808089267,"score_gpt":0.2192755949143848,"score_spread":0.2069254568334921,"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."}}