{"id":"W2353706530","doi":"","title":"Detection method against SYN Flooding attacks based on source end by analysis of time series","year":2012,"lang":"en","type":"article","venue":"Jisuanji yingyong yanjiu","topic":"Network Security and Intrusion Detection","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"The Alberta Paraplegic Foundation","funders":"","keywords":"Computer science; Flooding (psychology); Bloom filter; Data mining; Real-time computing; Time series; Denial-of-service attack; Network packet; Computer security; The Internet; Algorithm; Machine learning","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001310502,0.000260663,0.0004610388,0.000679408,0.0003436426,0.0001313073,0.0004793697,0.0001962325,0.0001228273],"category_scores_gemma":[0.0001276795,0.0002574023,0.0003125601,0.002340373,0.00005640831,0.0009440967,0.0001517819,0.0002961722,0.000069341],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001163091,"about_ca_system_score_gemma":0.00002429175,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006458887,"about_ca_topic_score_gemma":0.00002099269,"domain_scores_codex":[0.997656,0.0003613433,0.00045615,0.000472161,0.0005513004,0.0005030541],"domain_scores_gemma":[0.9983997,0.0003032609,0.000329702,0.0006813542,0.0001061757,0.0001798388],"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":[0.0002965713,0.001046038,0.007113158,0.0001613299,0.001528477,0.000007592974,0.003987709,0.1472488,0.2976289,0.001544778,0.002625724,0.536811],"study_design_scores_gemma":[0.0002339358,0.0001843027,0.001373978,0.0000458875,0.0002163469,0.000003710274,0.0000361126,0.8256759,0.1639594,0.00003528081,0.007922512,0.0003126852],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2592253,0.00014668,0.7381924,0.0001213808,0.000482875,0.0001417464,0.000007290868,0.0002694562,0.001412822],"genre_scores_gemma":[0.9888697,0.00001876587,0.01022668,0.0003637719,0.0001737333,0.00001391612,0.0000162916,0.00002230036,0.0002948086],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7296445,"threshold_uncertainty_score":0.9999878,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01114496445439657,"score_gpt":0.2569453766105736,"score_spread":0.245800412156177,"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."}}