{"id":"W3145232927","doi":"10.18280/ijsse.110106","title":"Intrusion Detection Models Using Supervised and Unsupervised Algorithms - A Comparative Estimation","year":2021,"lang":"en","type":"article","venue":"International Journal of Safety and Security Engineering","topic":"Network Security and Intrusion Detection","field":"Computer Science","cited_by":22,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Random forest; Computer science; Naive Bayes classifier; Machine learning; Intrusion detection system; Decision tree; Bayes' theorem; Data mining; Identification (biology); Outlier; Artificial intelligence; Classifier (UML); Anomaly detection; Algorithm; Support vector machine; Bayesian probability","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004969655,0.0008287087,0.0009697234,0.00239912,0.0004091834,0.00180573,0.001153884,0.0009844721,0.0009452754],"category_scores_gemma":[0.01562818,0.0004292643,0.00110487,0.00134887,0.0006866719,0.003823289,0.0008027526,0.001177417,0.000517434],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001172319,"about_ca_system_score_gemma":0.00105085,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003921892,"about_ca_topic_score_gemma":0.003019585,"domain_scores_codex":[0.9966165,0.001429785,0.0001808522,0.0005740893,0.001080532,0.0001182018],"domain_scores_gemma":[0.9864472,0.009454457,0.0007828532,0.001214325,0.001974498,0.0001266879],"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":[0.000219116,0.0003225906,0.02118631,0.0001695828,0.0003944762,0.00004457054,0.0001546213,0.648097,0.001055164,0.01679399,0.002002248,0.3095603],"study_design_scores_gemma":[0.000004735985,0.00005445102,0.002392804,0.00001756515,0.00002122296,0.00003289442,0.00002563819,0.9907106,0.0004535383,0.005531562,0.0007431221,0.00001182006],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07366893,0.002465982,0.917676,0.0005057393,0.00007086226,0.0001234206,0.0001872344,0.0008217074,0.004480134],"genre_scores_gemma":[0.7749612,0.002177871,0.2183448,0.0001290635,0.0002280173,0.0002069624,0.000756145,0.0001824041,0.00301359],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004969655,"threshold_uncertainty_score":0.02628237,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01994198000678464,"score_gpt":0.2472459965666037,"score_spread":0.2273040165598191,"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."}}