{"id":"W4413073828","doi":"10.1109/tnsm.2025.3589901","title":"A Game Theoretic Model for Strategic Defence Selection Against DDoS Attacks in IoT Networks","year":2025,"lang":"en","type":"article","venue":"IEEE Transactions on Network and Service Management","topic":"Network Security and Intrusion Detection","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Trent University; Ontario Tech University; University of Regina","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Denial-of-service attack; Application layer DDoS attack; Computer security; Game theory; Selection (genetic algorithm); Computer network; Botnet; Trinoo; Distributed computing; Artificial intelligence; The Internet","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0004038053,0.0002407247,0.0002177557,0.0002515937,0.0003739451,0.0001903041,0.0003890145,0.0001402674,0.000005271656],"category_scores_gemma":[4.766925e-7,0.00024898,0.00008298639,0.001500363,0.00003039077,0.0001784442,0.00001346999,0.0003150869,0.000003903976],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009605317,"about_ca_system_score_gemma":0.00003296518,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002099116,"about_ca_topic_score_gemma":0.0009113653,"domain_scores_codex":[0.9983343,0.00009175616,0.0003486531,0.0005913105,0.0001618137,0.0004721417],"domain_scores_gemma":[0.9993174,0.0001041928,0.00009072386,0.0003454661,0.00006977439,0.00007246398],"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":[0.00009455877,0.00009780809,0.000005578734,0.0001109962,0.00004024963,0.000001712333,0.0001593174,0.9144579,0.000005005082,0.03205911,0.0001070465,0.05286077],"study_design_scores_gemma":[0.0007259441,0.00009510971,0.00004751551,0.0002144553,0.00003908059,0.000001601403,0.00005711424,0.9750124,0.0000294164,0.02308534,0.0004725955,0.0002194225],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01632458,0.0001210581,0.9790532,0.0008542508,0.0006152691,0.000827923,0.000001291791,0.0001705517,0.002031865],"genre_scores_gemma":[0.9872006,0.001272519,0.006608258,0.004194496,0.00006353223,0.0003234298,0.000002450718,0.00001369361,0.00032099],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.972445,"threshold_uncertainty_score":0.9999962,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01522612685071359,"score_gpt":0.2386626754014074,"score_spread":0.2234365485506938,"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."}}