{"id":"W1964853784","doi":"10.1007/s10922-010-9176-7","title":"Trust Management and Admission Control for Host-Based Collaborative Intrusion Detection","year":2010,"lang":"en","type":"article","venue":"Journal of Network and Systems Management","topic":"Access Control and Trust","field":"Social Sciences","cited_by":24,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Intrusion detection system; Trustworthiness; Incentive; Computer security; Host (biology); Network security; Robustness (evolution); Trust management (information system); Intrusion; Control (management); Collaborative network; Computer network; Knowledge management; 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":[0.009004825,0.0005556849,0.001746932,0.001057877,0.001671274,0.004377714,0.00230647,0.001499861,0.001354711],"category_scores_gemma":[0.03674369,0.0005441349,0.0007246893,0.0008340855,0.002401726,0.004547264,0.002868424,0.002727543,0.0002044422],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002538806,"about_ca_system_score_gemma":0.002904215,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006752754,"about_ca_topic_score_gemma":0.005285511,"domain_scores_codex":[0.993534,0.002540743,0.000579488,0.0008609642,0.001531347,0.0009534582],"domain_scores_gemma":[0.9699689,0.01866249,0.00331672,0.003111916,0.003437524,0.001502429],"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":[0.002281641,0.0008928965,0.01863484,0.0001557527,0.000441922,0.0006005992,0.001740208,0.6299549,0.01285828,0.1220641,0.00353282,0.206842],"study_design_scores_gemma":[0.00001729471,0.00004514747,0.000450346,0.000003692115,0.00002581993,0.00003715139,0.00003924672,0.9865893,0.001117572,0.01150094,0.0001591482,0.00001435087],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1590905,0.0003489263,0.8369359,0.0007344147,0.0001309574,0.0001444598,0.0000401929,0.0006296146,0.001944947],"genre_scores_gemma":[0.9847157,0.00003670466,0.01462796,0.00002671627,0.00004042671,0.00002281932,0.00001461813,0.0000124497,0.0005027095],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.009004825,"threshold_uncertainty_score":0.04762268,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009060541253302924,"score_gpt":0.265276020429717,"score_spread":0.2562154791764141,"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."}}