{"id":"W4285106051","doi":"10.1109/access.2022.3176317","title":"Design and Development of RNN Anomaly Detection Model for IoT Networks","year":2022,"lang":"en","type":"article","venue":"IEEE Access","topic":"Network Security and Intrusion Detection","field":"Computer Science","cited_by":247,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ontario Tech University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Deep learning; Artificial intelligence; Recurrent neural network; Anomaly detection; Convolutional neural network; Machine learning; Intrusion detection system; Artificial neural network; Data mining","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":[0.000490765,0.0007296149,0.0005460232,0.0004850125,0.0003813003,0.0005908067,0.001608958,0.0007239112,0.001916462],"category_scores_gemma":[0.0006878813,0.0003797343,0.0006225342,0.0003588726,0.0003154613,0.0009120191,0.0005170454,0.001089573,0.0007477668],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001012111,"about_ca_system_score_gemma":0.001076335,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01479855,"about_ca_topic_score_gemma":0.009085217,"domain_scores_codex":[0.9997273,0.00003068821,0.00002107796,0.00009991686,0.00008595392,0.00003501115],"domain_scores_gemma":[0.9997683,0.00003662404,0.00002593991,0.00001652925,0.0001400841,0.00001257105],"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":[0.0000881743,0.00005661098,0.001571908,0.00007563484,0.00004813671,0.0001266794,0.00004963822,0.858192,0.01170096,0.006461532,0.001693461,0.1199353],"study_design_scores_gemma":[0.0000015897,0.000009865012,0.00005937885,0.000001887997,0.000003631645,0.00001000039,0.000001477462,0.9981903,0.0009553084,0.0004641517,0.0002998347,0.000002517295],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.009968404,0.0002025689,0.986096,0.0001489081,0.00005618015,0.00005087322,0.0000951859,0.001395671,0.001986138],"genre_scores_gemma":[0.7344968,0.0006094714,0.2552328,0.0002118236,0.00006715675,0.0003995981,0.0005423496,0.0001694899,0.008270547],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01479855,"threshold_uncertainty_score":0.02942485,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05390829886113963,"score_gpt":0.2737549412225625,"score_spread":0.2198466423614229,"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."}}