{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001595112,0.00009528448,0.00008870237,0.0001456496,0.0001624031,0.0001100444,0.0005555198,0.00003598634,0.0001828432],"category_scores_gemma":[0.00009446107,0.00008802897,0.00003030332,0.0004660074,0.000025855,0.00044845,0.0004156366,0.0001173599,0.000684087],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003320898,"about_ca_system_score_gemma":0.00001105873,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003619778,"about_ca_topic_score_gemma":0.00003377142,"domain_scores_codex":[0.9991237,0.00003030521,0.0001314121,0.0003341092,0.0001703808,0.0002101265],"domain_scores_gemma":[0.9993116,0.00002594336,0.00003691925,0.0003971317,0.0001282604,0.0001001971],"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":[0.00003278803,0.00007773395,0.003027463,0.00002162749,0.00002431238,0.00005721471,0.001735068,0.0001415294,0.08298751,0.05290259,0.01321048,0.8457817],"study_design_scores_gemma":[0.0002390277,0.0009327334,0.003440098,0.00002505787,0.000002819222,0.0001043377,0.00004302254,0.02321205,0.5993222,0.01508754,0.3570759,0.000515237],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.003718519,0.0000191903,0.9834945,0.0005235838,0.0002175864,0.0001141952,5.171817e-7,0.00183848,0.01007344],"genre_scores_gemma":[0.6722556,0.000004339208,0.3223684,0.0008274209,0.00008190899,0.00001507801,5.486271e-7,0.000009648089,0.004437088],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8452665,"threshold_uncertainty_score":0.8792783,"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."}}