{"id":"W4360997187","doi":"10.1109/aiipcc57291.2022.00011","title":"An Intelligent Network Intrusion Detector Using Deep Learning Model","year":2022,"lang":"en","type":"article","venue":"","topic":"Network Security and Intrusion Detection","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ontario Tech University","funders":"","keywords":"Intrusion detection system; Computer science; Decision tree; Vulnerability (computing); Network security; Scope (computer science); Computer security; Artificial intelligence; Set (abstract data type); Intrusion; Control (management); Tree (set theory); Machine learning; Data mining","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":["sts"],"consensus_categories":[],"category_scores_codex":[0.0005992601,0.0001327887,0.0001294922,0.000107381,0.001325309,0.0001552905,0.0007214482,0.00004600595,0.0004554032],"category_scores_gemma":[0.00001181676,0.0001361131,0.00006585362,0.0006892318,0.00001841534,0.0005336462,0.0008803208,0.0004882069,0.0000153368],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001578542,"about_ca_system_score_gemma":0.00004024113,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006082788,"about_ca_topic_score_gemma":0.00003681001,"domain_scores_codex":[0.9983293,0.0002686225,0.0002422803,0.000424573,0.0003733393,0.0003619201],"domain_scores_gemma":[0.9992949,0.00003852099,0.00009725201,0.0004035589,0.00004568724,0.0001201152],"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":[0.00001243859,0.00003219842,0.00004712632,0.000001473403,0.000003606993,0.00000320587,0.0004756915,0.8745022,0.001436452,0.009328517,0.00006051419,0.1140966],"study_design_scores_gemma":[0.00008142849,0.0002497897,0.00001601847,0.000003512863,0.000003594707,0.00003036694,0.00007800969,0.9858172,0.0009898196,0.008543898,0.003999499,0.0001868861],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1699956,0.0001178769,0.8283026,0.00004743881,0.0006546419,0.0001060529,1.583801e-7,0.000335983,0.0004396279],"genre_scores_gemma":[0.9178272,0.0000241457,0.08131238,0.0004748096,0.0002208304,0.00001475696,0.000002179612,0.00001358102,0.0001100744],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7478316,"threshold_uncertainty_score":0.9999748,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02347611902916412,"score_gpt":0.2520034362456263,"score_spread":0.2285273172164622,"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."}}