{"id":"W92356772","doi":"10.1007/978-3-642-38323-6_12","title":"Impact of Dataset Representation on Smartphone Malware Detection Performance","year":2013,"lang":"en","type":"book-chapter","venue":"IFIP advances in information and communication technology","topic":"Advanced Malware Detection Techniques","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":false,"ca_institutions":"École de Technologie Supérieure","funders":"","keywords":"Computer science; Classifier (UML); Malware; Representation (politics); Machine learning; Artificial intelligence; Android (operating system); System call; Factor (programming language); Data mining; Computer security; 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":[0.003881568,0.001587979,0.001397374,0.002417759,0.0007575694,0.003263334,0.00128412,0.00162321,0.002606322],"category_scores_gemma":[0.02123007,0.0003378093,0.001288538,0.002748065,0.0004513988,0.005250788,0.001638862,0.001483173,0.00206807],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001095386,"about_ca_system_score_gemma":0.00149901,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005524783,"about_ca_topic_score_gemma":0.006428596,"domain_scores_codex":[0.996753,0.0008057426,0.0003207628,0.0009609032,0.0008436913,0.0003158877],"domain_scores_gemma":[0.989477,0.005793635,0.0004694514,0.002544164,0.001290554,0.0004251279],"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":[0.006081296,0.001878998,0.0601538,0.001513723,0.001062189,0.0004028955,0.0001830635,0.05640749,0.02939956,0.001615369,0.1640032,0.6772984],"study_design_scores_gemma":[0.0006327271,0.002269711,0.0512128,0.000473443,0.001139619,0.002059493,0.001056819,0.8313513,0.06163698,0.007170747,0.04079058,0.0002056817],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8500648,0.01041653,0.0251242,0.006779413,0.003358406,0.0004236974,0.06463572,0.03069419,0.008503087],"genre_scores_gemma":[0.8313769,0.002265866,0.04030012,0.001034946,0.0005222583,0.000150737,0.1195356,0.0008483257,0.003965299],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005524783,"threshold_uncertainty_score":0.02052796,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01113769223611509,"score_gpt":0.287616576727222,"score_spread":0.2764788844911069,"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."}}