{"id":"W4389543387","doi":"10.1109/csnet59123.2023.10339748","title":"IDS with deep learning techniques","year":2023,"lang":"en","type":"article","venue":"","topic":"Network Security and Intrusion Detection","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Computer science; Intrusion detection system; Artificial intelligence; Deep learning; Machine learning; Artificial neural network; Deep neural networks; Intrusion; Binary number; Recurrent neural network; Multiclass classification; Binary classification; Data mining; Support vector machine","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001533901,0.00004514884,0.00004439028,0.00007990522,0.0001246044,0.00007482462,0.00019813,0.00002835261,0.00004427606],"category_scores_gemma":[0.000007043714,0.00003337995,0.00001426909,0.0006913889,0.000013527,0.0002524229,0.0001080847,0.000106429,0.0001994296],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000007923522,"about_ca_system_score_gemma":0.000006246108,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001439036,"about_ca_topic_score_gemma":0.00002072975,"domain_scores_codex":[0.9995295,0.00002363831,0.00005565587,0.0001441261,0.0001188273,0.0001282925],"domain_scores_gemma":[0.9997625,0.00002459716,0.00001740664,0.0001411731,0.00002592307,0.00002843359],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000006465852,0.0000129545,0.000465521,0.000006404954,0.00000731546,0.0000223723,0.0005774359,0.0003365004,0.001493703,0.08439223,0.002554162,0.910125],"study_design_scores_gemma":[0.0001866076,0.0008103679,0.00237002,0.00003847294,0.000003203043,0.00005702877,0.0001141652,0.5510716,0.08802956,0.01081226,0.3461362,0.0003705746],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01721608,0.00001467953,0.9482985,0.0005917767,0.0001034471,0.00006669858,1.934332e-8,0.00307133,0.0306375],"genre_scores_gemma":[0.941437,0.0000839964,0.05402495,0.0003365691,0.0001126532,0.00001995931,0.000001032132,0.000007917291,0.003975912],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9242209,"threshold_uncertainty_score":0.256333,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00898844738727948,"score_gpt":0.2242171917934794,"score_spread":0.2152287444061999,"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."}}