{"id":"W4400975400","doi":"10.1109/accai61061.2024.10601954","title":"Machine Learning Approaches for Anomaly Detection in IoT Networks","year":2024,"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":"Horizon College and Seminary","funders":"","keywords":"Anomaly detection; Computer science; Internet of Things; Artificial intelligence; Anomaly (physics); Machine learning; Computer security","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":[0.002877263,0.0007736931,0.0006753178,0.003101595,0.0006190101,0.002136288,0.001554317,0.001158325,0.001014159],"category_scores_gemma":[0.01154139,0.0003441111,0.0007727396,0.001927104,0.001724426,0.002736721,0.001355137,0.002089952,0.0002691977],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00143858,"about_ca_system_score_gemma":0.0008608428,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002719302,"about_ca_topic_score_gemma":0.002134878,"domain_scores_codex":[0.9984733,0.0007535021,0.0001031192,0.0002798541,0.0002875733,0.0001026835],"domain_scores_gemma":[0.9926812,0.005558612,0.000638667,0.0004420808,0.0005646126,0.0001148074],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00008598019,0.0002404934,0.01769947,0.0003352456,0.0002415377,0.0003003859,0.0007620653,0.5540226,0.002006353,0.1586031,0.001953112,0.2637497],"study_design_scores_gemma":[0.00000318814,0.00001907768,0.0006621354,0.00002318832,0.000008799464,0.00004763137,0.00007716676,0.9220781,0.000388367,0.07579958,0.0008821377,0.00001061503],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01589839,0.001201594,0.979563,0.0008919999,0.00004427582,0.00004418078,0.00004648649,0.0002321768,0.002077947],"genre_scores_gemma":[0.7277271,0.001737124,0.2668191,0.0002688532,0.0002577704,0.0001733932,0.0001596734,0.00005622741,0.002800695],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003101595,"threshold_uncertainty_score":0.01521659,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02496634888085203,"score_gpt":0.2254994380774832,"score_spread":0.2005330891966311,"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."}}