{"id":"W2921161567","doi":"10.5220/0007470705280535","title":"The Curious Case of Machine Learning in Malware Detection","year":2019,"lang":"en","type":"article","venue":"","topic":"Advanced Malware Detection Techniques","field":"Computer Science","cited_by":45,"is_retracted":false,"has_abstract":true,"ca_institutions":"Thompson Rivers University; University of Windsor","funders":"","keywords":"Malware; Computer science; Artificial intelligence; Computer security; Machine learning; Natural language processing","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":[0.000243931,0.0000654227,0.00008038983,0.00009412791,0.00007541819,0.00002691216,0.0002432964,0.00003495514,0.0000118618],"category_scores_gemma":[0.00006045884,0.00004697431,0.00002919261,0.0003443821,0.000017465,0.0002470051,0.000137932,0.0001872639,0.0000177043],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003741013,"about_ca_system_score_gemma":0.00001176722,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003577453,"about_ca_topic_score_gemma":0.0009528657,"domain_scores_codex":[0.9993845,0.0000568186,0.000167116,0.0001726749,0.00008845192,0.0001304068],"domain_scores_gemma":[0.9994049,0.0001324118,0.00008058875,0.0003157953,0.00004753126,0.00001878782],"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":[0.0000200233,0.00002811309,0.00271971,0.00002175901,0.000005771513,0.0001558236,0.000355144,0.001666786,0.01399426,0.01011755,0.00001295224,0.9709021],"study_design_scores_gemma":[0.0005905991,0.0006542417,0.001459784,0.00003069103,0.000002458386,0.00223278,0.0002554016,0.47541,0.4938738,0.01177294,0.01338505,0.0003321983],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1452751,0.00009734544,0.8523625,0.0001231139,0.0001547852,0.0001995355,2.531046e-7,0.0004159537,0.001371393],"genre_scores_gemma":[0.9884134,0.000021768,0.0107275,0.00003127744,0.000005645181,0.00001180928,1.09049e-7,0.000005472522,0.0007830159],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9705699,"threshold_uncertainty_score":0.1915557,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005067674708644204,"score_gpt":0.2402839224914033,"score_spread":0.2352162477827591,"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."}}