{"id":"W1511785468","doi":"10.1109/snpd-sawn.2005.31","title":"DIDMA: A Distributed Intrusion Detection System Using Mobile Agents","year":2005,"lang":"en","type":"article","venue":"","topic":"Network Security and Intrusion Detection","field":"Computer Science","cited_by":74,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"Computer science; Intrusion detection system; Computer security","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":[0.001185183,0.001012094,0.001062262,0.00120952,0.0007155116,0.001643614,0.002337532,0.001396578,0.002070066],"category_scores_gemma":[0.003284235,0.0005670713,0.00053579,0.0005154113,0.0006122855,0.001813927,0.001545026,0.001244417,0.001197015],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000579922,"about_ca_system_score_gemma":0.0009671173,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001407527,"about_ca_topic_score_gemma":0.0009771005,"domain_scores_codex":[0.9991598,0.0001611574,0.0001080168,0.0002082334,0.0002852618,0.00007746951],"domain_scores_gemma":[0.9985637,0.0004511495,0.0001898891,0.0002851346,0.0003110215,0.0001991244],"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":[0.002954934,0.001230005,0.01446418,0.001379373,0.00088291,0.002164532,0.001259239,0.08013092,0.1173118,0.02974483,0.05249692,0.6959803],"study_design_scores_gemma":[0.001257048,0.00110315,0.003007336,0.00009385638,0.0004034796,0.001600805,0.0001234585,0.7230257,0.06775818,0.01249882,0.188913,0.000215158],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03279805,0.0008568681,0.8928466,0.0005154299,0.0004481043,0.001328766,0.00058864,0.06484655,0.005770968],"genre_scores_gemma":[0.3719004,0.0007206766,0.6107563,0.0005843794,0.0002081866,0.001377898,0.001905687,0.0005505463,0.0119959],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002337532,"threshold_uncertainty_score":0.006925046,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0150405289182683,"score_gpt":0.2402249227898919,"score_spread":0.2251843938716236,"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."}}