{"id":"W2028521711","doi":"10.1109/cicybs.2014.7013367","title":"Supervised learning to detect DDoS attacks","year":2014,"lang":"en","type":"article","venue":"","topic":"Network Security and Intrusion Detection","field":"Computer Science","cited_by":44,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"National Institute for Materials Science; Natural Sciences and Engineering Research Council of Canada; Dalhousie University","keywords":"Computer science; Machine learning; Decision tree; Artificial intelligence; Naive Bayes classifier; Denial-of-service attack; Intrusion detection system; Supervised learning; Feature (linguistics); Random forest; Open source; Support vector machine; The Internet; Artificial neural network; World Wide Web; Software; Operating system","routes":{"ca_aff":true,"ca_fund":true,"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":[0.00347289,0.0009974203,0.001219046,0.001660935,0.000450237,0.0008142457,0.00102447,0.0008662794,0.001041063],"category_scores_gemma":[0.01254291,0.0003153933,0.0005953548,0.0007765227,0.0004708733,0.0011458,0.0006291997,0.00107405,0.0006773608],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006993885,"about_ca_system_score_gemma":0.0009903937,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001873035,"about_ca_topic_score_gemma":0.00206343,"domain_scores_codex":[0.9970994,0.001272567,0.0002323081,0.0005021889,0.0007300797,0.0001635051],"domain_scores_gemma":[0.9858657,0.009682976,0.0009835962,0.00108038,0.002209597,0.0001778502],"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":[0.0004530773,0.0009954709,0.01378335,0.000254117,0.0004391428,0.0001077326,0.0001006928,0.4833541,0.005769471,0.002470442,0.005303536,0.4869689],"study_design_scores_gemma":[0.00001703653,0.00008412091,0.001001377,0.000009347784,0.0000173661,0.00002971663,0.00001394044,0.9933226,0.002837867,0.002218914,0.0004399368,0.000007796821],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1473326,0.001014894,0.8427708,0.000429119,0.0001936143,0.0002590891,0.0004449218,0.004136573,0.003418233],"genre_scores_gemma":[0.8105116,0.0002352685,0.1855357,0.0002491599,0.0001604658,0.0002496525,0.001046656,0.0001135811,0.001897892],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00347289,"threshold_uncertainty_score":0.01836663,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01205789869431697,"score_gpt":0.2318059030510762,"score_spread":0.2197480043567592,"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."}}