{"id":"W4386809635","doi":"10.18280/ria.370405","title":"Feature Selection for Android Malware Detection with Random Forest on Smartphones","year":2023,"lang":"en","type":"article","venue":"Revue d intelligence artificielle","topic":"Advanced Malware Detection Techniques","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Random forest; Android malware; Malware; Feature selection; Android (operating system); Computer science; Artificial intelligence; Computer security; Data mining; Machine learning; Operating system","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003411268,0.0002222011,0.0002164937,0.0003492673,0.0004086634,0.000128267,0.0004048848,0.0001246797,0.000007889713],"category_scores_gemma":[0.0002514941,0.0001962662,0.0001075759,0.001659876,0.00004905886,0.000413906,0.00006525722,0.0002220285,0.0001752813],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009181889,"about_ca_system_score_gemma":0.00003050494,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001102337,"about_ca_topic_score_gemma":0.0001681881,"domain_scores_codex":[0.9984819,0.0000445793,0.0002232122,0.0006353321,0.0002067239,0.0004083041],"domain_scores_gemma":[0.9986173,0.0003119965,0.0001377791,0.0004957326,0.0003547145,0.00008248991],"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":[0.001230839,0.0001998167,0.0006570054,0.0002575958,0.00006344912,0.00002705716,0.0009715459,0.3348981,0.0400107,0.009939851,0.008409481,0.6033346],"study_design_scores_gemma":[0.0001467548,0.0007963261,0.0001023917,0.0000664468,0.000006283382,0.00003909696,0.00009921154,0.4270334,0.5473269,0.004355025,0.01979321,0.0002349765],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01313489,0.00002769456,0.9828728,0.0006671186,0.0005288672,0.0008342027,0.00000501691,0.001690964,0.0002383845],"genre_scores_gemma":[0.9700976,0.00005815057,0.024971,0.0001386978,0.0002306213,0.0006204762,0.00001255083,0.00004432016,0.00382657],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9579018,"threshold_uncertainty_score":0.8003502,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02174793365251056,"score_gpt":0.264837927184046,"score_spread":0.2430899935315354,"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."}}