{"id":"W4296467084","doi":"10.3390/computers11100142","title":"Efficient, Lightweight Cyber Intrusion Detection System for IoT Ecosystems Using MI2G Algorithm","year":2022,"lang":"en","type":"article","venue":"Computers","topic":"Network Security and Intrusion Detection","field":"Computer Science","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"","keywords":"Computer science; Internet of Things; Feature selection; Intrusion detection system; Algorithm; Reduction (mathematics); The Internet; Feature (linguistics); Data mining; Machine learning; Entropy (arrow of time); Artificial intelligence; Intrusion; 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":[0.0004372371,0.0009771404,0.001090053,0.001274073,0.0004557875,0.0006879587,0.0009376075,0.0006951854,0.0007652609],"category_scores_gemma":[0.0009147056,0.0001875922,0.0005042895,0.0008288358,0.0001982303,0.0007535467,0.0005409631,0.00054577,0.0004319791],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005695926,"about_ca_system_score_gemma":0.0006450628,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003335528,"about_ca_topic_score_gemma":0.00325093,"domain_scores_codex":[0.9997037,0.00004112137,0.00002682738,0.00008507886,0.00009748332,0.00004577334],"domain_scores_gemma":[0.9998037,0.00005524104,0.0000279025,0.0000265639,0.00007300091,0.00001362371],"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":[0.0006503172,0.0005105285,0.01077417,0.0001278149,0.0002093657,0.0003250301,0.0001019198,0.1920113,0.03143676,0.003216179,0.01564648,0.7449901],"study_design_scores_gemma":[0.00002683452,0.00008053708,0.001653895,0.000004330438,0.00001509711,0.00009236405,0.00001975802,0.9911609,0.004414478,0.0009719838,0.001548896,0.00001087952],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1743956,0.001143484,0.8106021,0.0005568325,0.0003529587,0.000350074,0.0005577669,0.007815548,0.004225499],"genre_scores_gemma":[0.6808045,0.0004050843,0.3127506,0.0002299442,0.0001027135,0.0003782107,0.00180268,0.0000977454,0.003428524],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003335528,"threshold_uncertainty_score":0.006632268,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01351141658442858,"score_gpt":0.2199100060707584,"score_spread":0.2063985894863298,"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."}}