{"id":"W4308000139","doi":"10.1186/s13677-022-00349-8","title":"A malware detection system using a hybrid approach of multi-heads attention-based control flow traces and image visualization","year":2022,"lang":"en","type":"article","venue":"Journal of Cloud Computing Advances Systems and Applications","topic":"Advanced Malware Detection Techniques","field":"Computer Science","cited_by":43,"is_retracted":false,"has_abstract":true,"ca_institutions":"Brandon University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Malware; Android (operating system); Artificial intelligence; Android malware; Support vector machine; Machine learning; Pattern recognition (psychology); Operating system","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0007780301,0.0001512145,0.0003784838,0.0002681215,0.0005700848,0.0001029878,0.00027765,0.00003117988,2.701123e-7],"category_scores_gemma":[0.00002198781,0.0001493553,0.00008121736,0.0004576752,0.00006266523,0.0003693647,0.00007079337,0.0001927738,7.769014e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001373025,"about_ca_system_score_gemma":0.00005396843,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001818691,"about_ca_topic_score_gemma":6.963767e-7,"domain_scores_codex":[0.9982032,0.0002349491,0.0007840374,0.0002837516,0.0003400839,0.0001540467],"domain_scores_gemma":[0.9977006,0.0001550368,0.001449383,0.0002179429,0.0004014403,0.00007562276],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00007641193,0.0003985829,0.001024471,0.001699941,0.00009290313,0.000009367563,0.0003542951,0.8559727,0.05543261,0.007279516,0.00001113479,0.07764804],"study_design_scores_gemma":[0.0007489309,0.0001865039,0.0001044306,0.0001228526,0.00003288669,0.0006549794,0.0006831154,0.9938487,0.002705561,0.000121926,0.000648417,0.0001417146],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03406043,0.0027329,0.9622297,0.00001301651,0.0002430368,0.000567777,0.00002050427,0.000123233,0.000009399922],"genre_scores_gemma":[0.8619141,0.00001753398,0.137854,0.000009728011,0.0001271395,0.00005986491,0.000001665451,0.00001332411,0.000002703785],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8278537,"threshold_uncertainty_score":0.6090533,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01181556239907689,"score_gpt":0.2725403864438092,"score_spread":0.2607248240447323,"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."}}