{"id":"W4402289221","doi":"10.1016/j.jocs.2024.102426","title":"DeepDetect: An innovative hybrid deep learning framework for anomaly detection in IoT networks","year":2024,"lang":"en","type":"article","venue":"Journal of Computational Science","topic":"Network Security and Intrusion Detection","field":"Computer Science","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"Brandon University","funders":"Eesti Teadusagentuur","keywords":"Anomaly detection; Internet of Things; Computer science; Deep learning; Anomaly (physics); Artificial intelligence; Computer architecture; Embedded system; Physics","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":[0.0006228271,0.0007518689,0.0006512785,0.0006580872,0.0002776651,0.0008221109,0.001845654,0.0008992811,0.00128015],"category_scores_gemma":[0.0008833096,0.0003870462,0.0006472984,0.0005728689,0.0004966619,0.00126107,0.001516497,0.001473062,0.0003268204],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008800917,"about_ca_system_score_gemma":0.0009671542,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008381079,"about_ca_topic_score_gemma":0.01188844,"domain_scores_codex":[0.9997247,0.0000459952,0.00001378729,0.00006090062,0.0001011662,0.00005336992],"domain_scores_gemma":[0.9997733,0.00007110287,0.00002694818,0.00002348396,0.00008114211,0.00002395116],"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":[0.0002043073,0.0001739709,0.002685821,0.0001156821,0.0001540137,0.0001750381,0.00007561641,0.6777902,0.008615762,0.01902112,0.007322483,0.2836659],"study_design_scores_gemma":[0.000002300639,0.00001098346,0.00007697442,0.000002650869,0.000003303093,0.00001040464,0.00000239524,0.9964406,0.0004941876,0.00244714,0.0005061314,0.000002912743],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01404353,0.0004994613,0.9815478,0.000240111,0.00006814236,0.0000341521,0.0002454193,0.00199928,0.001322178],"genre_scores_gemma":[0.6380007,0.0008976393,0.3502096,0.0005815053,0.0001140124,0.0001993293,0.001564518,0.000296073,0.008136706],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008381079,"threshold_uncertainty_score":0.01666456,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01181268811116041,"score_gpt":0.2844666334273097,"score_spread":0.2726539453161492,"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."}}