{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001234076,0.001352501,0.001179032,0.002747378,0.0005396758,0.0005418672,0.0007503976,0.0006857589,0.000857224],"category_scores_gemma":[0.003399335,0.0003253667,0.001716862,0.001192607,0.0002396901,0.0007400382,0.0005146053,0.0007519209,0.0008778935],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003512231,"about_ca_system_score_gemma":0.0007200735,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009349435,"about_ca_topic_score_gemma":0.009532119,"domain_scores_codex":[0.9991936,0.0001785541,0.00006283111,0.0002168336,0.0002071927,0.0001410777],"domain_scores_gemma":[0.9987466,0.0007378098,0.00009443036,0.0001070136,0.0002633209,0.0000507445],"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":[0.0009160254,0.0004751524,0.01886103,0.0002817636,0.0002435747,0.0009026282,0.0001756824,0.1409995,0.02707781,0.0008584496,0.0112065,0.7980019],"study_design_scores_gemma":[0.00003587443,0.000118348,0.003897852,0.0000199858,0.00005173979,0.000268822,0.00004915153,0.9868985,0.006160211,0.001136374,0.001340741,0.00002233339],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3323627,0.002362425,0.6432961,0.0004814975,0.0001920218,0.0002981806,0.002002035,0.01750098,0.001503953],"genre_scores_gemma":[0.7249036,0.0004430278,0.2678611,0.0001386889,0.0001051863,0.0002460875,0.004701428,0.0002527046,0.001348162],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.009349435,"threshold_uncertainty_score":0.01859003,"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."}}