{"id":"W2547748649","doi":"10.1109/ccece.2016.7726677","title":"Machine learning techniques for intrusion detection on public dataset","year":2016,"lang":"en","type":"article","venue":"","topic":"Network Security and Intrusion Detection","field":"Computer Science","cited_by":60,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"","keywords":"Computer science; Intrusion detection system; Feature (linguistics); Data mining; Machine learning; Reduction (mathematics); Software deployment; Intrusion; Artificial intelligence","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":[0.002877244,0.001634778,0.001035273,0.005095407,0.0008579526,0.001024416,0.001812268,0.001155001,0.001527255],"category_scores_gemma":[0.008102165,0.0002829066,0.001513635,0.004280511,0.0003450602,0.001121336,0.0009601361,0.001575682,0.001252933],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001240528,"about_ca_system_score_gemma":0.00167823,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006656797,"about_ca_topic_score_gemma":0.007101725,"domain_scores_codex":[0.9972901,0.0004842003,0.000522341,0.0005058951,0.0008866744,0.0003107688],"domain_scores_gemma":[0.9959701,0.001335769,0.0003534858,0.001081346,0.001143432,0.0001157975],"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":[0.001304577,0.003983826,0.0474115,0.001092895,0.0008404122,0.0009503439,0.0003833783,0.1064557,0.01473802,0.002906287,0.1365508,0.6833823],"study_design_scores_gemma":[0.0002968373,0.0009776634,0.0563321,0.0001029824,0.0001830129,0.001099735,0.0005361092,0.8481854,0.03226338,0.0040764,0.05581783,0.0001285311],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6502553,0.002379906,0.1106446,0.001364176,0.0007158127,0.002482193,0.1915466,0.03237193,0.008239378],"genre_scores_gemma":[0.46968,0.0005371071,0.2108402,0.000157796,0.0001362442,0.002521473,0.3124876,0.000302727,0.003336903],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006656797,"threshold_uncertainty_score":0.01521653,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02148583372371401,"score_gpt":0.2522199463563,"score_spread":0.2307341126325859,"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."}}