{"id":"W2799960805","doi":"10.1109/iscas.2018.8351647","title":"Evaluation of Support Vector Machine Kernels for Detecting Network Anomalies","year":2018,"lang":"en","type":"article","venue":"","topic":"Network Security and Intrusion Detection","field":"Computer Science","cited_by":23,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Support vector machine; Border Gateway Protocol; Computer science; Anomaly detection; Convergence (economics); Routing protocol; Distance-vector routing protocol; Anomaly (physics); Default-free zone; Machine learning; Artificial intelligence; The Internet; Data mining; Routing (electronic design automation); Computer network; Static routing","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":[0.004801953,0.001054277,0.001340322,0.00207402,0.0003328974,0.001188206,0.0009355418,0.001104234,0.0005152834],"category_scores_gemma":[0.01693303,0.0001999673,0.0005496528,0.001214075,0.000375391,0.001609994,0.0006571111,0.0007778762,0.0002961454],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006802431,"about_ca_system_score_gemma":0.0006180068,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0036786,"about_ca_topic_score_gemma":0.001335757,"domain_scores_codex":[0.9971916,0.0008583372,0.0003468932,0.0003308765,0.001037894,0.0002344792],"domain_scores_gemma":[0.9867147,0.007702766,0.0009120632,0.0008176582,0.003439026,0.0004138554],"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":[0.003929858,0.001179967,0.03661162,0.0004853201,0.0004930847,0.0002552031,0.0001306637,0.5017282,0.01474866,0.001719439,0.0032003,0.4355177],"study_design_scores_gemma":[0.00001679614,0.0002611085,0.003499949,0.000008955029,0.00002286121,0.00004604819,0.00002816045,0.9920066,0.003765341,0.0001907689,0.0001418611,0.00001147553],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.875661,0.002863032,0.1171869,0.0002575972,0.0001905522,0.00009894179,0.0003869,0.001855389,0.001499777],"genre_scores_gemma":[0.9773145,0.0002446405,0.02154395,0.0000155496,0.00001880508,0.00002228238,0.0004973282,0.0000335759,0.0003094336],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004801953,"threshold_uncertainty_score":0.02539551,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03977164240815087,"score_gpt":0.2956290652907381,"score_spread":0.2558574228825872,"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."}}