{"id":"W2000773362","doi":"10.1109/comswa.2007.382483","title":"APHIDS++: A Mobile Agent Based Intrusion Detection System","year":2007,"lang":"en","type":"article","venue":"","topic":"Network Security and Intrusion Detection","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Intrusion detection system; Computer science; Mobile agent; Computer security; Computer network","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":[],"consensus_categories":[],"category_scores_codex":[0.0008061017,0.0001211052,0.0001120414,0.0002117335,0.0002526486,0.0001043259,0.0003337927,0.0001071792,0.00005804241],"category_scores_gemma":[0.00001131448,0.0001060264,0.00007872193,0.0006808838,0.00001920296,0.0003191552,0.0001211699,0.0001456199,0.0002001198],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001638767,"about_ca_system_score_gemma":0.00001995111,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009038184,"about_ca_topic_score_gemma":0.0001499052,"domain_scores_codex":[0.9987276,0.00005642473,0.0002767201,0.0003395905,0.0003139608,0.0002856888],"domain_scores_gemma":[0.9992128,0.00006951945,0.00008169522,0.0004289699,0.00008521308,0.0001217991],"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":[0.0000700136,0.0001298815,0.0000516338,0.00006382422,0.00001112723,0.00004190642,0.0002797021,0.001154796,0.02812758,0.02028045,0.0006239645,0.9491651],"study_design_scores_gemma":[0.0004641433,0.0004431838,0.0004341246,0.00005074076,0.000005873425,0.00006172727,0.0001190063,0.6528536,0.3029607,0.0003126577,0.04201294,0.0002813182],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06691758,0.00005121082,0.9259697,0.00004374273,0.001421422,0.0002472246,1.966407e-7,0.0007362089,0.004612764],"genre_scores_gemma":[0.9866656,0.000004874687,0.01269458,0.0002773924,0.0002103403,0.00002264443,6.08008e-7,0.000007227377,0.0001167492],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9488838,"threshold_uncertainty_score":0.432363,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008534649901150609,"score_gpt":0.2191159150503356,"score_spread":0.210581265149185,"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."}}