{"id":"W4229730853","doi":"10.13052/2245-1439.523","title":"SMS-Based Mobile Botnet Detection Framework Using Intelligent Agents","year":2017,"lang":"en","type":"article","venue":"Journal of Cyber Security and Mobility","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":"","keywords":"Botnet; Android (operating system); Exploit; Malware; Computer science; Computer security; Phishing; Short Message Service; Android malware; Computer network; The Internet; World Wide Web; Operating system","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":[],"consensus_categories":[],"category_scores_codex":[0.001414952,0.0001678482,0.0003042455,0.0001115094,0.0007387465,0.0004718689,0.0007064604,0.0002012921,0.00004311404],"category_scores_gemma":[0.0002643066,0.0001497007,0.00018436,0.0001185003,0.0001701313,0.001143299,0.00025344,0.0006356906,0.000003229051],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001050736,"about_ca_system_score_gemma":0.00008538716,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001359332,"about_ca_topic_score_gemma":0.00008459953,"domain_scores_codex":[0.9983606,0.0001796355,0.0005301746,0.0002922802,0.0003935352,0.0002437509],"domain_scores_gemma":[0.997894,0.0001276377,0.0007574893,0.0007379163,0.0002754552,0.0002074606],"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":[0.001269312,0.00406328,0.01418057,0.0005180872,0.0003925124,0.0002531593,0.01440699,0.009169943,0.00761832,0.007514231,0.0006168456,0.9399967],"study_design_scores_gemma":[0.002176208,0.002743641,0.0403177,0.0007546262,0.0001641188,0.000566355,0.0003348472,0.64121,0.1050459,0.1642623,0.04133196,0.001092383],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7379862,0.0003711937,0.2598453,0.0001266591,0.001401582,0.0001560536,0.000001576006,0.0000209471,0.00009051542],"genre_scores_gemma":[0.9940711,0.0001596341,0.005261234,0.0001786869,0.0003133197,0.0000040985,1.890959e-7,0.000006667165,0.000005048363],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9389043,"threshold_uncertainty_score":0.6104618,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02727318133157571,"score_gpt":0.3039755979040534,"score_spread":0.2767024165724777,"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."}}