{"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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0003178475,0.00007904386,0.00008780034,0.00007829181,0.0001707362,0.0001336953,0.0004135039,0.00004657239,0.0001715787],"category_scores_gemma":[0.0001028684,0.00007017893,0.00004131047,0.0003543795,0.00000825104,0.0002336441,0.0002053136,0.0001448535,0.000793295],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001530652,"about_ca_system_score_gemma":0.000008346462,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003017432,"about_ca_topic_score_gemma":0.00003293399,"domain_scores_codex":[0.9991531,0.00009481172,0.000117013,0.0002613147,0.0001633067,0.0002104727],"domain_scores_gemma":[0.99945,0.00007221734,0.00002838812,0.0002923263,0.00004257081,0.0001145291],"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":[0.000008202891,0.00001123336,0.0002385813,0.000005293994,0.000004950976,0.000001458052,0.000652061,0.002352952,0.005328865,0.01546479,0.003882441,0.9720492],"study_design_scores_gemma":[0.0002557002,0.000472462,0.001447554,0.00001380509,0.00000192906,0.00001081512,0.00001703299,0.6834882,0.02114938,0.002791964,0.2900985,0.0002525407],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1051595,0.000009302261,0.878878,0.0007532767,0.0003504182,0.00007628946,2.920831e-8,0.0003735984,0.0143996],"genre_scores_gemma":[0.9649073,0.000004302922,0.03222775,0.001517653,0.0001573064,0.000007715353,2.490642e-7,0.000005655532,0.001172011],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9717966,"threshold_uncertainty_score":0.9999847,"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."}}