{"id":"W4390874756","doi":"10.1109/gcaiot61060.2023.10385112","title":"Security of SDN in an Adversarial Setting: The DDoS Case","year":2023,"lang":"en","type":"article","venue":"","topic":"Software-Defined Networks and 5G","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University; Royal Military College of Canada","funders":"","keywords":"Denial-of-service attack; Computer science; Adversarial machine learning; Cripple; Computer security; Software-defined networking; Adversarial system; Malware; Botnet; Evasion (ethics); Network security; Field (mathematics); Network management; Artificial intelligence; Sandbox (software development); Computer network; The Internet; Software engineering; Operating system","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":[0.0004842723,0.00006253887,0.0000860751,0.00005703614,0.00006049106,0.00004117534,0.0004389284,0.00004082233,0.00001970338],"category_scores_gemma":[0.00004733116,0.00004162528,0.00003362522,0.0007018779,0.00002729125,0.0001851697,0.0002312046,0.0001021866,0.00002206805],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000008923971,"about_ca_system_score_gemma":0.00003497809,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004017456,"about_ca_topic_score_gemma":0.0005857027,"domain_scores_codex":[0.9992652,0.00007396015,0.0001502353,0.0001888414,0.0001338475,0.0001879147],"domain_scores_gemma":[0.9992309,0.000246887,0.00003697366,0.0004181396,0.00002718552,0.00003994654],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001150245,0.0006928649,0.1328572,0.0001047147,0.00008134233,0.008750536,0.05315525,0.02757695,0.0003544775,0.4261392,0.1070302,0.2431423],"study_design_scores_gemma":[0.0009266818,0.0001611118,0.01180894,0.00001902689,0.000005773478,0.0002224343,0.0007543587,0.9632197,0.0004324528,0.01934045,0.002864355,0.0002447091],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9752476,0.0000291373,0.02021599,0.00189213,0.000633362,0.0001937215,0.000003508428,0.0003633075,0.001421281],"genre_scores_gemma":[0.9982994,0.000003178671,0.001310754,0.0002309298,0.00008683675,0.000005401876,0.000001576504,0.000003780901,0.0000581652],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9356428,"threshold_uncertainty_score":0.169743,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01804466614734831,"score_gpt":0.2688425923776652,"score_spread":0.2507979262303169,"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."}}