{"id":"W2072729826","doi":"10.1145/1501434.1501515","title":"Design and implementation of a behavioral difference analyzer for network intrusion detection","year":2006,"lang":"en","type":"article","venue":"","topic":"Network Security and Intrusion Detection","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of New Brunswick","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Intrusion detection system; Redundancy (engineering); Computer science; Server; Differential (mechanical device); Spectrum analyzer; Intrusion; Computer network; Real-time computing; Data mining; Engineering; Operating system; Telecommunications","routes":{"ca_aff":true,"ca_fund":true,"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":[0.001636229,0.0008694179,0.0008505402,0.00180848,0.0006057385,0.001404054,0.002386298,0.0007599334,0.002631381],"category_scores_gemma":[0.004186559,0.0005730013,0.0003674016,0.0006056883,0.0005634121,0.001662307,0.0007503508,0.0009956477,0.0009284331],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008434512,"about_ca_system_score_gemma":0.001053876,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009568225,"about_ca_topic_score_gemma":0.0007665721,"domain_scores_codex":[0.9981161,0.0004082765,0.0001940161,0.0003623494,0.0007262529,0.0001929324],"domain_scores_gemma":[0.9964839,0.001248007,0.0003089073,0.0003906734,0.001357205,0.0002113898],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.002057927,0.0008998702,0.01408912,0.0006093121,0.0003613651,0.000867457,0.0010222,0.02556334,0.2974955,0.02715453,0.009850333,0.6200291],"study_design_scores_gemma":[0.0003586948,0.001718104,0.003785393,0.00007219194,0.0002740206,0.001518852,0.0001982355,0.6317277,0.3317264,0.007014562,0.02144492,0.0001609331],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02088146,0.0001047897,0.969242,0.0001371109,0.00008163234,0.0005089457,0.00008510956,0.007251747,0.001707202],"genre_scores_gemma":[0.3302753,0.00009099348,0.6662498,0.0002636971,0.00006097756,0.0006752553,0.000269379,0.000287904,0.00182671],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002631381,"threshold_uncertainty_score":0.008802891,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01830801751464112,"score_gpt":0.275391108143737,"score_spread":0.2570830906290959,"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."}}