{"id":"W2076952382","doi":"10.1007/s11416-014-0222-y","title":"Sliding window and control flow weight for metamorphic malware detection","year":2014,"lang":"en","type":"article","venue":"Journal of Computer Virology and Hacking Techniques","topic":"Advanced Malware Detection Techniques","field":"Computer Science","cited_by":25,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Victoria","funders":"","keywords":"Opcode; Computer science; Malware; Control flow; Sliding window protocol; Compiler; Feature (linguistics); Artificial intelligence; Data mining; Window (computing); Operating system; Programming language","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":[0.001178772,0.0001919159,0.0004400409,0.0003952859,0.0002268666,0.0001104262,0.0003612346,0.0001921002,0.000001030898],"category_scores_gemma":[0.00007761941,0.0001671157,0.0001050643,0.0001112548,0.00008272781,0.0007012388,0.000146399,0.0003362076,2.262654e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002645957,"about_ca_system_score_gemma":0.00001562889,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001239988,"about_ca_topic_score_gemma":0.000001977438,"domain_scores_codex":[0.9987167,0.00018035,0.0004521612,0.0002861155,0.0001326733,0.0002320007],"domain_scores_gemma":[0.9985542,0.0004099802,0.0004752616,0.0002265124,0.0002447301,0.00008926668],"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":[0.0001373488,0.00003502774,0.0004873275,0.00005312072,0.00008632471,0.00001496244,0.0001429447,0.00004902993,0.0402396,0.01062434,0.0001451523,0.9479848],"study_design_scores_gemma":[0.002347226,0.006012631,0.006425745,0.0002319784,0.0001504536,0.003731142,0.000005568409,0.2655812,0.4627534,0.2166737,0.03539466,0.0006923396],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01006399,0.0002873013,0.98786,0.0008589932,0.0003221253,0.0002343579,0.000001017326,0.0003575956,0.00001460779],"genre_scores_gemma":[0.5483701,0.00007529971,0.4507402,0.0005227006,0.0002662702,0.00001363364,1.404651e-7,0.000009482783,0.000002220413],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9472924,"threshold_uncertainty_score":0.6814781,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006507935392993599,"score_gpt":0.2258057382333638,"score_spread":0.2192978028403702,"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."}}