{"id":"W4395675681","doi":"10.18280/ijsse.140218","title":"Enhanced Malware Detection for Mobile Operating Systems Using Machine Learning and Dynamic Analysis","year":2024,"lang":"en","type":"article","venue":"International Journal of Safety and Security Engineering","topic":"Advanced Malware Detection Techniques","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Malware; Embedded system; Artificial intelligence; Machine learning; Real-time computing; Computer security","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":[0.0003401572,0.00009551138,0.0001689217,0.0004444826,0.00007153826,0.0002516842,0.0001439326,0.00004446716,0.000001293188],"category_scores_gemma":[0.00007088551,0.00009303031,0.00007881473,0.0002342113,0.000009430095,0.0006471107,0.00007113129,0.0002236662,7.661841e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001193961,"about_ca_system_score_gemma":0.00001455546,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000136308,"about_ca_topic_score_gemma":0.000006874118,"domain_scores_codex":[0.9992492,0.00001774928,0.0003158216,0.0001536968,0.0001705911,0.00009296548],"domain_scores_gemma":[0.9994698,0.0001387225,0.0001032691,0.00004386409,0.0001993689,0.00004500536],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00005019411,0.00001577313,0.00006633683,0.0002191088,0.0009251783,0.00005112242,0.001585691,0.7481078,0.1850759,0.002499566,2.617394e-7,0.06140309],"study_design_scores_gemma":[0.0001213715,0.00007213865,0.00003670577,0.0001370918,0.00004192044,0.0002733376,0.00005755523,0.9874073,0.01078046,0.0001281006,0.0008519202,0.00009205555],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07402571,0.002634082,0.92255,0.00003146449,0.000570777,0.0000804183,0.000007534419,0.00009695643,0.000003060658],"genre_scores_gemma":[0.9708847,0.0005348614,0.02846505,0.000004425668,0.00008674702,0.000005455097,0.00000182554,0.000008808446,0.00000814345],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.896859,"threshold_uncertainty_score":0.3793666,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004083255879205305,"score_gpt":0.2600220230381302,"score_spread":0.2559387671589248,"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."}}