{"id":"W2040146912","doi":"10.1109/infcomw.2014.6849283","title":"Behavioral analytics for inferring large-scale orchestrated probing events","year":2014,"lang":"en","type":"article","venue":"","topic":"Network Security and Intrusion Detection","field":"Computer Science","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Computer science; Exploit; Malware; Context (archaeology); Computer security; Event (particle physics); The Internet; Data science; Botnet; Cyberspace; Analytics; Task (project management); World Wide Web","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":[0.000866156,0.001189582,0.0005579276,0.003587137,0.00032641,0.001098957,0.001040965,0.0007441693,0.0009600588],"category_scores_gemma":[0.004889747,0.0003359955,0.0005501751,0.001834221,0.0004389868,0.001670024,0.0008887334,0.001151369,0.000470513],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005886629,"about_ca_system_score_gemma":0.0008028009,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006257683,"about_ca_topic_score_gemma":0.007049776,"domain_scores_codex":[0.9992785,0.0001711031,0.00006247339,0.0001988208,0.0002269787,0.00006227281],"domain_scores_gemma":[0.9968334,0.001644725,0.0006203918,0.0003613582,0.0003777799,0.0001623739],"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":[0.0004132231,0.001180151,0.1771106,0.0005894994,0.0004786476,0.0008410622,0.0008966096,0.4615272,0.03135121,0.03026902,0.007446863,0.2878958],"study_design_scores_gemma":[0.000004622915,0.00004022801,0.007953961,0.00001592958,0.00001816432,0.00006103083,0.0001445699,0.9761457,0.001858394,0.01265948,0.001083536,0.00001435293],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1683716,0.0004585522,0.8185604,0.0007010561,0.00005467784,0.0002389834,0.004040956,0.004339074,0.003234651],"genre_scores_gemma":[0.8581915,0.0002989723,0.1366745,0.000130062,0.00005799386,0.0001735933,0.003542757,0.0000949137,0.000835631],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006257683,"threshold_uncertainty_score":0.01244253,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03070908730024404,"score_gpt":0.2812500738414376,"score_spread":0.2505409865411936,"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."}}