{"id":"W2000058312","doi":"10.1145/2567926","title":"Mitigating DoS Attacks Using Performance Model-Driven Adaptive Algorithms","year":2014,"lang":"en","type":"article","venue":"ACM Transactions on Autonomous and Adaptive Systems","topic":"Network Security and Intrusion Detection","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University; York University","funders":"Natural Sciences and Engineering Research Council of Canada; Amazon Catalyst; International Business Machines Corporation","keywords":"Computer science; Denial-of-service attack; Scalability; Firewall (physics); Computer security; Computer network; The Internet; Algorithm; Distributed computing; World Wide Web; Database","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":[0.001683686,0.001330906,0.0008281671,0.0008738571,0.0004741127,0.001401163,0.001514038,0.0007823734,0.0009706343],"category_scores_gemma":[0.005401887,0.000384597,0.0005052918,0.0004247372,0.0006558935,0.001206149,0.0008959472,0.001433667,0.0003851964],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001051401,"about_ca_system_score_gemma":0.001162472,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003681502,"about_ca_topic_score_gemma":0.003122675,"domain_scores_codex":[0.9990736,0.0002245877,0.00005296534,0.0002175393,0.0003052579,0.0001259971],"domain_scores_gemma":[0.9974419,0.001306292,0.0004176811,0.0002817786,0.000457597,0.00009477999],"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":[0.00007739947,0.0001180448,0.001464442,0.00002486464,0.00003428363,0.00002368592,0.00003617414,0.9440322,0.003844355,0.003006282,0.0005654696,0.04677279],"study_design_scores_gemma":[0.000004376499,0.00001819154,0.00007096214,0.000002097454,0.000004795381,0.000005424367,0.000003398794,0.9979334,0.0006297927,0.001191716,0.0001326992,0.000003095885],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04990317,0.0002694823,0.9438075,0.0003329544,0.00005805995,0.0001193803,0.00003722018,0.002527001,0.002945237],"genre_scores_gemma":[0.8742632,0.0001844016,0.1237556,0.0001314946,0.00004179769,0.0001403923,0.00007716536,0.0001118313,0.001294088],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003681502,"threshold_uncertainty_score":0.008904278,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03509982188862211,"score_gpt":0.2440907167487519,"score_spread":0.2089908948601298,"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."}}