{"id":"W2792488777","doi":"10.1002/itl2.31","title":"Accuracy or delay? A game in detecting interest flooding attacks","year":2018,"lang":"en","type":"article","venue":"Internet Technology Letters","topic":"Caching and Content Delivery","field":"Computer Science","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Fundamental Research Funds for the Central Universities; Natural Science Foundation of Shandong Province; National Natural Science Foundation of China","keywords":"Computer science; Flooding (psychology); Network packet; Computer network; Router; Computer security; Real-time computing","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":[0.0002470575,0.0002056422,0.0002264742,0.0007941946,0.00005025372,0.0001458384,0.001753169,0.0001791995,0.00002353646],"category_scores_gemma":[0.0003333928,0.0001834059,0.00006738495,0.0007125176,0.0002207677,0.0004074978,0.0008506098,0.0006097165,0.0002488069],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001330098,"about_ca_system_score_gemma":0.00002427012,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001767332,"about_ca_topic_score_gemma":0.0009576358,"domain_scores_codex":[0.9983897,0.00005233509,0.0003536248,0.0005831629,0.0001174322,0.0005037862],"domain_scores_gemma":[0.998959,0.0001588369,0.000130656,0.0006577207,0.00004844851,0.00004533617],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002402233,0.0002072026,0.0311914,0.00004302412,0.0002097683,0.003172605,0.004599593,0.00004668205,0.3502208,0.01933675,0.009337578,0.5813944],"study_design_scores_gemma":[0.008411038,0.003489899,0.003030656,0.00355931,0.00008285348,0.007897819,0.002420103,0.5076163,0.3917428,0.005386852,0.0618831,0.004479313],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8450615,0.00005594793,0.1459122,0.007306005,0.0006685937,0.000106443,4.42398e-7,0.0007090375,0.000179822],"genre_scores_gemma":[0.9942654,0.000005194719,0.002361027,0.003119391,0.0001027888,0.00002574039,4.451193e-7,0.00001642538,0.0001036023],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.576915,"threshold_uncertainty_score":0.7479075,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03436938044368684,"score_gpt":0.275800473607103,"score_spread":0.2414310931634161,"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."}}