{"id":"W1480870385","doi":"10.1007/11801412_8","title":"Detecting Impersonation Attacks in Future Wireless and Mobile Networks","year":2006,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Network Security and Intrusion Detection","field":"Computer Science","cited_by":87,"is_retracted":false,"has_abstract":false,"ca_institutions":"Carleton University","funders":"","keywords":"Computer science; Computer security; Intrusion detection system; Wireless; Wireless network; Simple (philosophy); Wireless sensor network; Intrusion; Computer network; Telecommunications","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":[0.0006227749,0.0005987116,0.0004880483,0.001067024,0.0003818419,0.001147185,0.0007839403,0.001219395,0.002212846],"category_scores_gemma":[0.004097491,0.0003567852,0.0002712575,0.0004894249,0.0003795795,0.003461951,0.0006730324,0.000869369,0.001039331],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003800497,"about_ca_system_score_gemma":0.0002203136,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006440182,"about_ca_topic_score_gemma":0.0008956523,"domain_scores_codex":[0.9992557,0.0000898294,0.00003543646,0.00009684396,0.0004081049,0.0001141291],"domain_scores_gemma":[0.9975311,0.001208092,0.0003154846,0.0004005358,0.0004762695,0.00006851635],"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":[0.0004663882,0.0002715735,0.02549076,0.0003177997,0.00009093102,0.001540148,0.0006098056,0.0581641,0.05305058,0.01520478,0.01365729,0.8311358],"study_design_scores_gemma":[0.00003154143,0.0006310762,0.0164372,0.0001363452,0.0001529731,0.008472087,0.0006068836,0.8047531,0.1013955,0.03013098,0.03717656,0.00007573824],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4632587,0.006133888,0.4829131,0.001142999,0.0004339262,0.0002195421,0.0004372029,0.005057382,0.04040335],"genre_scores_gemma":[0.9222271,0.001871084,0.06100157,0.0001415103,0.0001439737,0.00003283901,0.0004260058,0.0001603049,0.0139957],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002212846,"threshold_uncertainty_score":0.007402718,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007022978214900874,"score_gpt":0.2187895115624919,"score_spread":0.211766533347591,"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."}}