{"id":"W3115696055","doi":"10.1109/isncc49221.2020.9297264","title":"Polymorphic Adversarial DDoS attack on IDS using GAN","year":2020,"lang":"en","type":"article","venue":"","topic":"Adversarial Robustness in Machine Learning","field":"Computer Science","cited_by":53,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ontario Tech University","funders":"","keywords":"Computer science; Adversarial system; Denial-of-service attack; Intrusion detection system; Generative adversarial network; Adversarial machine learning; Artificial intelligence; Graphics; Computer security; Generative grammar; Machine learning; Deep learning; World Wide Web; Operating system; The Internet","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000181566,0.0002123321,0.0002199331,0.00007978683,0.0002097978,0.0001559948,0.001112772,0.00009372389,0.0002302812],"category_scores_gemma":[0.0002275132,0.0001978731,0.00009927787,0.000557082,0.00004684196,0.0005096691,0.0004112701,0.0003888497,0.0003450373],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006572466,"about_ca_system_score_gemma":0.0001086772,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006467921,"about_ca_topic_score_gemma":0.000001846945,"domain_scores_codex":[0.9982176,0.000129228,0.0002441968,0.0005875224,0.0004455442,0.0003758748],"domain_scores_gemma":[0.9990444,0.0001170007,0.0001015279,0.0004724633,0.0000402741,0.0002243265],"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":[0.0001485495,0.00009907257,0.002697867,0.0000333063,0.00008149798,0.0002303283,0.002722494,0.7909901,0.007239901,0.1745814,0.003120554,0.01805499],"study_design_scores_gemma":[0.000698444,0.0001577456,0.0002690156,0.0000140023,0.000009438148,0.000009999541,0.00003593613,0.9934102,0.00129535,0.0001886462,0.003621504,0.0002897732],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0239627,0.00001011956,0.9559507,0.00587952,0.0008461386,0.0001407957,8.223976e-7,0.0005034734,0.01270571],"genre_scores_gemma":[0.922726,8.316226e-7,0.07196382,0.004307392,0.0007574554,0.000001608765,0.00000145676,0.00002217176,0.0002192794],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8987633,"threshold_uncertainty_score":0.8069032,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09998868787046503,"score_gpt":0.3145216271929053,"score_spread":0.2145329393224403,"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."}}