{"id":"W4246413350","doi":"10.32920/ryerson.14647329","title":"Detection and mitigation of SYN and HTTP flood DDoS attacks in software defined networks","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Network Security and Intrusion Detection","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"Advanced Research Projects Agency; Defense Advanced Research Projects Agency","keywords":"Denial-of-service attack; Internet Control Message Protocol; Computer science; Spoofing attack; Computer security; Application layer DDoS attack; Flood myth; Computer network; Network security; Network packet; The Internet; Geography","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":[0.0007571529,0.0004041861,0.0005315999,0.001062168,0.0003098158,0.0005056652,0.000522352,0.0005501722,0.0002567329],"category_scores_gemma":[0.002100794,0.0001821822,0.0002885418,0.0003889476,0.0002710324,0.0009946892,0.0005884102,0.0003688513,0.0001202504],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003195891,"about_ca_system_score_gemma":0.0004686311,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004184914,"about_ca_topic_score_gemma":0.0002529578,"domain_scores_codex":[0.9989821,0.0001859045,0.0001229749,0.0001457602,0.000451973,0.0001112172],"domain_scores_gemma":[0.9986902,0.0002758092,0.0003646432,0.0002121029,0.0003869057,0.00007032198],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001150421,0.0006835691,0.02275592,0.0005534001,0.0001839628,0.0007999976,0.0003790811,0.08018818,0.3741329,0.007459266,0.00283715,0.508876],"study_design_scores_gemma":[0.00007755131,0.001399796,0.01816309,0.0001029602,0.0001328435,0.001959947,0.0002791862,0.6078204,0.3581324,0.003057379,0.008771501,0.0001029352],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7036368,0.002213335,0.2850948,0.0004202208,0.0002201648,0.0002684045,0.0001381016,0.001558621,0.006449515],"genre_scores_gemma":[0.9673333,0.0005286602,0.0310762,0.00006701556,0.00002759203,0.0000461423,0.0001064927,0.00001162722,0.0008029035],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001062168,"threshold_uncertainty_score":0.0040043,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009324662901209091,"score_gpt":0.217869884431685,"score_spread":0.2085452215304759,"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."}}