{"id":"W2130876900","doi":"10.1002/ett.2502","title":"Combating channel eviction triggering denial‐of‐service attacks in cognitive radio networks","year":2012,"lang":"en","type":"article","venue":"Transactions on Emerging Telecommunications Technologies","topic":"Cognitive Radio Networks and Spectrum Sensing","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Denial-of-service attack; Cognitive radio; Computer security; Adversary; Computer science; Eviction; Computer network; Incentive; Class (philosophy); Channel (broadcasting); Focus (optics); Service (business); Telecommunications; Business; The Internet; Wireless; Economics","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0005518073,0.0002347377,0.0003178017,0.0007424664,0.0005127458,0.00005487141,0.0009496014,0.0001895206,0.000009399902],"category_scores_gemma":[0.00006603296,0.0002564102,0.0001044575,0.002649406,0.0001159658,0.000714898,0.00007374132,0.0008101798,0.000006875655],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001440427,"about_ca_system_score_gemma":0.00003113597,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001088105,"about_ca_topic_score_gemma":0.0002748361,"domain_scores_codex":[0.9983228,0.0001496075,0.0005175161,0.0002971554,0.0001758386,0.0005370294],"domain_scores_gemma":[0.997941,0.0006862895,0.0002231578,0.0009529539,0.0001517127,0.00004495307],"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":[0.00004491445,0.001028656,0.001133322,0.00004610917,0.0002056761,0.000002547887,0.00431364,0.07793982,0.0004486121,0.009502831,0.00003256718,0.9053013],"study_design_scores_gemma":[0.001122277,0.0001541185,0.005285034,0.0008269094,0.00008173667,0.00005352005,0.005134345,0.9744053,0.01027802,0.001474837,0.0004500066,0.0007338714],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04185849,0.001748812,0.9501979,0.003748627,0.0002283524,0.0003428294,0.000002746224,0.001098204,0.0007739721],"genre_scores_gemma":[0.9697034,0.001493592,0.02858442,0.0000741618,0.00002057126,0.00008711924,0.000005844311,0.00002134507,0.000009561762],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9278449,"threshold_uncertainty_score":0.9999888,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03060816990913249,"score_gpt":0.2847513342362225,"score_spread":0.2541431643270899,"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."}}