{"id":"W2967309414","doi":"10.1109/uemcon.2018.8796795","title":"Machine Learning to Identify Android Malware","year":2018,"lang":"en","type":"article","venue":"","topic":"Advanced Malware Detection Techniques","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"British Columbia Institute of Technology","funders":"","keywords":"Malware; Android malware; Computer science; Android (operating system); Machine learning; Artificial intelligence; Android application; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001626215,0.0007978076,0.0006736311,0.003706099,0.000488861,0.001192494,0.0005293036,0.0009400939,0.000962207],"category_scores_gemma":[0.006964072,0.0002070667,0.0006061347,0.001524201,0.0003830355,0.001199447,0.0004261014,0.001018568,0.0008645419],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005719943,"about_ca_system_score_gemma":0.0005395233,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002021222,"about_ca_topic_score_gemma":0.002192755,"domain_scores_codex":[0.9984143,0.0004056153,0.0001253439,0.0002548582,0.0006606844,0.0001392567],"domain_scores_gemma":[0.9953376,0.003005663,0.0003719705,0.0003312887,0.0008769321,0.00007649857],"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":[0.0002408828,0.0007301025,0.046619,0.0004578899,0.0002930813,0.0003087583,0.00022738,0.07841153,0.01245861,0.005721428,0.007654419,0.8468769],"study_design_scores_gemma":[0.00002514612,0.0002749558,0.01424163,0.0001355901,0.00008242492,0.0004477724,0.0001497627,0.9488763,0.01562197,0.0111108,0.008983406,0.00005027317],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4299465,0.01176449,0.5291159,0.002372734,0.0009089276,0.0004882723,0.001354564,0.003833931,0.02021466],"genre_scores_gemma":[0.8798558,0.001478961,0.1140472,0.0002841013,0.0002371004,0.0001324114,0.0008640824,0.0000500558,0.003050248],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003706099,"threshold_uncertainty_score":0.008600295,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01417354543397789,"score_gpt":0.3098146746258025,"score_spread":0.2956411291918246,"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."}}