{"id":"W4386157204","doi":"10.32920/24033972.v1","title":"Detection and Mitigation of IP Spoofing and SYN Flooding DDoS Attacks in Cloud Computing","year":2023,"lang":"en","type":"preprint","venue":"","topic":"Network Security and Intrusion Detection","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"IP address spoofing; Denial-of-service attack; Spoofing attack; Computer science; Flooding (psychology); Cloud computing; ARP spoofing; Computer security; Computer network; Application layer DDoS attack; Ip address; Network security; The Internet; Internet Protocol; IP address management; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006530607,0.0005806618,0.0006353536,0.001656746,0.0004760158,0.0009257774,0.0006549812,0.0005829709,0.0005006431],"category_scores_gemma":[0.002467876,0.0001433697,0.0003878538,0.0009028956,0.000304167,0.001008708,0.0004413066,0.0003580284,0.0003065209],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006071982,"about_ca_system_score_gemma":0.001040713,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002676805,"about_ca_topic_score_gemma":0.001556922,"domain_scores_codex":[0.998792,0.0001665569,0.0001187131,0.0001763844,0.0005813565,0.0001649988],"domain_scores_gemma":[0.998828,0.0001968895,0.0002791207,0.0001586228,0.0004646979,0.00007263751],"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":[0.0008491327,0.0006336022,0.02351516,0.0003284954,0.000110897,0.000478315,0.0002132539,0.0935112,0.1342138,0.004831013,0.004542066,0.736773],"study_design_scores_gemma":[0.00004416961,0.0004028767,0.01166809,0.00005098486,0.00006466565,0.000674079,0.0001840681,0.8168692,0.1616471,0.001175161,0.007164873,0.0000547448],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6018313,0.002976483,0.3799149,0.0007056568,0.0003237456,0.0003441336,0.0002200699,0.003557896,0.01012574],"genre_scores_gemma":[0.8866539,0.000936106,0.1103299,0.000104759,0.00004134884,0.00005157841,0.0001864635,0.0000434873,0.001652487],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002676805,"threshold_uncertainty_score":0.005322397,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02420167257672952,"score_gpt":0.2591581004521452,"score_spread":0.2349564278754157,"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."}}