{"id":"W3185928824","doi":"10.3390/iot2030022","title":"Towards a Hybrid Deep Learning Model for Anomalous Activities Detection in Internet of Things Networks","year":2021,"lang":"en","type":"article","venue":"IoT","topic":"Network Security and Intrusion Detection","field":"Computer Science","cited_by":59,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ontario Tech University","funders":"","keywords":"Computer science; MQTT; Internet of Things; Botnet; Convolutional neural network; Anomaly detection; Intrusion detection system; Artificial intelligence; Computer network; Machine learning; Data mining; Computer security; The Internet; 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":[0.0008175503,0.0006803951,0.0005969,0.0005748338,0.0002411976,0.0007622314,0.001262016,0.0008509074,0.0007177493],"category_scores_gemma":[0.001237955,0.0003711324,0.00066303,0.0004639852,0.0003164284,0.0008351913,0.0007057724,0.001200394,0.0003411421],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008002563,"about_ca_system_score_gemma":0.0007810229,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01225623,"about_ca_topic_score_gemma":0.01043699,"domain_scores_codex":[0.999768,0.00004830924,0.00001619008,0.00007571094,0.0000452164,0.00004665319],"domain_scores_gemma":[0.9996371,0.0001447358,0.00004154468,0.00002698468,0.0001272262,0.0000223226],"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":[0.0001494146,0.0001721054,0.003890899,0.0000503822,0.0001180101,0.00008841263,0.00005391685,0.8249096,0.005124884,0.003376876,0.002115349,0.1599501],"study_design_scores_gemma":[8.475863e-7,0.00000648036,0.00007104152,0.000001573117,0.000002439472,0.000002948185,0.000001358185,0.9993174,0.0001944017,0.0003454289,0.00005488877,0.00000117632],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1278171,0.0009702435,0.8658498,0.0007195222,0.0001421881,0.00005427161,0.0002718072,0.001866741,0.002308431],"genre_scores_gemma":[0.9139726,0.0003711578,0.08023901,0.0002839401,0.00006062679,0.00009270029,0.0005346887,0.00006557025,0.004379731],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01225623,"threshold_uncertainty_score":0.02436978,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01210501563042712,"score_gpt":0.2246120079371497,"score_spread":0.2125069923067225,"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."}}