{"id":"W3012496643","doi":"10.1109/tnse.2020.2981449","title":"Minimizing Financial Cost of DDoS Attack Defense in Clouds With Fine-Grained Resource Management","year":2020,"lang":"en","type":"article","venue":"IEEE Transactions on Network Science and Engineering","topic":"Network Security and Intrusion Detection","field":"Computer Science","cited_by":22,"is_retracted":false,"has_abstract":true,"ca_institutions":"St. Francis Xavier University","funders":"Shenzhen Fundamental Research Program; China Postdoctoral Science Foundation; National Natural Science Foundation of China","keywords":"Denial-of-service attack; Computer science; Cloud computing; Computer security; Application layer DDoS attack; Resource (disambiguation); Popularity; Competition (biology); Computer network; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001503743,0.0009887989,0.001083014,0.001052517,0.001364631,0.002028529,0.001838446,0.0008674515,0.001513143],"category_scores_gemma":[0.00284419,0.000295468,0.0004373932,0.0009352495,0.000701158,0.003130967,0.001727603,0.0007645583,0.0002199551],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002374776,"about_ca_system_score_gemma":0.002873189,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004736841,"about_ca_topic_score_gemma":0.004491865,"domain_scores_codex":[0.998869,0.0002241782,0.00005522025,0.0001671051,0.0002789714,0.0004054306],"domain_scores_gemma":[0.9983668,0.0005194577,0.0003460703,0.0002589748,0.0002431373,0.0002655773],"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":[0.0008847448,0.0005166053,0.007829977,0.0003766769,0.00009445516,0.0004087246,0.0001579347,0.6721545,0.02725913,0.03998752,0.005576151,0.2447536],"study_design_scores_gemma":[0.00003071933,0.0001690072,0.001348585,0.0000147458,0.00004210193,0.0001674989,0.0001301849,0.9846671,0.00493173,0.006831968,0.001640125,0.00002618897],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4580572,0.006012782,0.5141015,0.00247321,0.0003751468,0.0005805264,0.0002708414,0.001743288,0.01638545],"genre_scores_gemma":[0.9839734,0.000251871,0.01519402,0.00006009117,0.00002046985,0.00003163177,0.0000249978,0.00001404558,0.0004293177],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004736841,"threshold_uncertainty_score":0.01723033,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01386475810231967,"score_gpt":0.2025352763156422,"score_spread":0.1886705182133226,"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."}}