{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005716951,0.0008052135,0.0006958108,0.003405293,0.0003816632,0.0007532588,0.0005102042,0.0004960125,0.0006434537],"category_scores_gemma":[0.001864714,0.0001992591,0.0005201718,0.00121332,0.000272028,0.001543071,0.0003619689,0.0005028297,0.0003018403],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002854945,"about_ca_system_score_gemma":0.0003218346,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001070495,"about_ca_topic_score_gemma":0.0007328675,"domain_scores_codex":[0.9993284,0.00007916019,0.00006382113,0.0001841739,0.0002921572,0.00005240584],"domain_scores_gemma":[0.9992077,0.0002025497,0.0001651834,0.00006626629,0.0003169097,0.00004137224],"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":[0.00061828,0.0003430189,0.04303614,0.0003874736,0.0002817055,0.0008639807,0.0006107477,0.08051528,0.08826996,0.01070328,0.004916638,0.7694536],"study_design_scores_gemma":[0.00002333074,0.0002050163,0.01342443,0.00002358708,0.00008980423,0.0007419151,0.0001528779,0.9446005,0.03343416,0.003171143,0.004072327,0.00006089708],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1267554,0.000591222,0.8671159,0.0001823996,0.0001575859,0.0001142715,0.0002265183,0.002051632,0.002805253],"genre_scores_gemma":[0.8854199,0.0005648385,0.1107365,0.0000603752,0.0001374925,0.00009547047,0.0004696419,0.00006187925,0.002453819],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003405293,"threshold_uncertainty_score":0.003023446,"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."}}