{"id":"W109441098","doi":"","title":"Alert Correlation for Extracting Attack Strategies","year":2006,"lang":"en","type":"article","venue":"","topic":"Network Security and Intrusion Detection","field":"Computer Science","cited_by":124,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of New Brunswick","funders":"","keywords":"Computer science; Intrusion detection system; Data mining; Probabilistic logic; Support vector machine; Cluster analysis; Computer security; Network security; Feature (linguistics); Machine learning; Artificial intelligence","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":[0.0007104937,0.001529714,0.0006400128,0.005916813,0.0004969062,0.00118035,0.0006721091,0.0006756561,0.003617679],"category_scores_gemma":[0.005441796,0.0003303035,0.00093441,0.003387592,0.0003110879,0.001838016,0.00074522,0.001080694,0.002096932],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004849625,"about_ca_system_score_gemma":0.001381396,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003085204,"about_ca_topic_score_gemma":0.002994548,"domain_scores_codex":[0.9986215,0.0001289862,0.0001751497,0.0003476271,0.0006111046,0.0001157385],"domain_scores_gemma":[0.9975919,0.0007760614,0.0003996971,0.0002421757,0.0009075335,0.00008271966],"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":[0.0002936194,0.0002604457,0.01189185,0.0003980005,0.0001327631,0.0004751332,0.0003337195,0.02677625,0.03134362,0.008548575,0.009349578,0.9101964],"study_design_scores_gemma":[0.00004255989,0.0003773517,0.01607291,0.0001125166,0.0001672988,0.001134888,0.0003522578,0.8940668,0.04845357,0.01476972,0.02434646,0.0001036336],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03596565,0.0004196913,0.9523142,0.000183334,0.0001336941,0.0004508005,0.001541094,0.005247021,0.003744533],"genre_scores_gemma":[0.3548948,0.0006778234,0.63508,0.0001574085,0.0001513523,0.0004440781,0.004405344,0.0002241836,0.003965055],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005916813,"threshold_uncertainty_score":0.01210231,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02316176158991253,"score_gpt":0.2664332177684348,"score_spread":0.2432714561785223,"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."}}