{"id":"W4382240482","doi":"10.1007/s11276-023-03414-5","title":"NMal-Droid: network-based android malware detection system using transfer learning and CNN-BiGRU ensemble","year":2023,"lang":"en","type":"article","venue":"Wireless Networks","topic":"Advanced Malware Detection Techniques","field":"Computer Science","cited_by":23,"is_retracted":false,"has_abstract":false,"ca_institutions":"Brandon University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Malware; Android (operating system); Convolutional neural network; Network packet; Artificial intelligence; Machine learning; Computer security; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002985895,0.00127615,0.000746911,0.001240307,0.0003439706,0.0004547923,0.001035396,0.0005262573,0.003653484],"category_scores_gemma":[0.0006378131,0.000256485,0.0003649658,0.0003495924,0.0001669523,0.00105736,0.0009296656,0.0005912599,0.001567733],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000511742,"about_ca_system_score_gemma":0.0004718803,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005271788,"about_ca_topic_score_gemma":0.008585262,"domain_scores_codex":[0.9997405,0.00002004464,0.00001035133,0.00007788541,0.0001013416,0.00004982574],"domain_scores_gemma":[0.9998229,0.00003506021,0.00001717453,0.00003328027,0.00006834838,0.00002329676],"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":[0.00144497,0.0007949467,0.01461323,0.0003891018,0.0003712704,0.0007357144,0.0001254832,0.02918314,0.06255272,0.001410056,0.05960739,0.8287721],"study_design_scores_gemma":[0.00009727438,0.0005398472,0.008120951,0.00002677565,0.0001177036,0.0005317248,0.00005574216,0.9033742,0.07686167,0.001060947,0.009138171,0.00007507869],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4291615,0.003901415,0.3742901,0.0008465354,0.001179836,0.0007796529,0.004922288,0.1652149,0.01970382],"genre_scores_gemma":[0.8608821,0.0005727001,0.1122167,0.0006316272,0.0001638859,0.0003088658,0.005981389,0.0007276501,0.01851507],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005271788,"threshold_uncertainty_score":0.01222217,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01165765042397046,"score_gpt":0.2343927391909054,"score_spread":0.222735088766935,"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."}}