{"id":"W4213282066","doi":"10.36227/techrxiv.19210197.v1","title":"Intrusion Detection in the IoT under Data and Concept Drifts: Online Deep Learning Approach","year":2022,"lang":"en","type":"preprint","venue":"","topic":"Data Stream Mining Techniques","field":"Computer Science","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec en Outaouais","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Concept drift; Computer science; Intrusion detection system; Anomaly detection; Artificial intelligence; Data mining; Weighting; Artificial neural network; Outlier; Data stream mining; Machine learning; Deep learning","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":[0.003020939,0.0009185711,0.001391436,0.001388869,0.0004855245,0.001227463,0.002150134,0.00141365,0.0004548182],"category_scores_gemma":[0.00677617,0.000554051,0.0007693524,0.001403384,0.0008710859,0.002161602,0.001753381,0.00249216,0.0001260404],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001400948,"about_ca_system_score_gemma":0.001361526,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006283176,"about_ca_topic_score_gemma":0.00381309,"domain_scores_codex":[0.9990576,0.000213385,0.00006287925,0.000211188,0.0002683935,0.0001865349],"domain_scores_gemma":[0.9974636,0.001319747,0.000347897,0.0001685498,0.0005424508,0.000157745],"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":[0.0002094621,0.0002488053,0.008875332,0.00009486703,0.0001482088,0.0002378375,0.0002185514,0.7932746,0.00211698,0.007123498,0.001799866,0.185652],"study_design_scores_gemma":[0.000001766219,0.000008744404,0.0001712889,0.00000222786,0.000003564452,0.000008323559,0.000006611572,0.9974704,0.0001989496,0.002056169,0.00007008228,0.000001972132],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1049288,0.0008887436,0.8912047,0.001012499,0.00007814207,0.00006236236,0.0001221608,0.0007380099,0.0009645923],"genre_scores_gemma":[0.9005755,0.0004840137,0.09639607,0.0003153922,0.0001267585,0.00008391236,0.0002708657,0.00006440051,0.001683064],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.006283176,"threshold_uncertainty_score":0.01597649,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05226221503555983,"score_gpt":0.307245136036827,"score_spread":0.2549829210012671,"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."}}