{"id":"W4285059789","doi":"10.1109/access.2022.3189645","title":"PAIRED: An Explainable Lightweight Android Malware Detection System","year":2022,"lang":"en","type":"article","venue":"IEEE Access","topic":"Advanced Malware Detection Techniques","field":"Computer Science","cited_by":64,"is_retracted":false,"has_abstract":true,"ca_institutions":"Seneca Polytechnic; Toronto Metropolitan University","funders":"","keywords":"Android (operating system); Malware; Computer science; Operating system; Mobile device; Embedded system; Android malware; Computer security; System call","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":[0.0003800812,0.000188973,0.0001940162,0.0003074168,0.0009340401,0.0003464551,0.001979688,0.00005821675,0.0000394009],"category_scores_gemma":[0.0000126833,0.0002023246,0.00006775655,0.0009854122,0.00002166964,0.003065093,0.0006202413,0.0002862949,0.0000157573],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004457677,"about_ca_system_score_gemma":0.00004961318,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001089704,"about_ca_topic_score_gemma":0.000030757,"domain_scores_codex":[0.9980273,0.0002110711,0.0002812077,0.0006466844,0.0004676557,0.0003661288],"domain_scores_gemma":[0.9985738,0.00004198707,0.0001874367,0.0009581502,0.0001157864,0.0001227734],"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":[0.0004062258,0.001203155,0.002017552,0.0008840741,0.000159495,0.002190229,0.004009742,0.02628377,0.1572417,0.02922302,0.01240415,0.7639769],"study_design_scores_gemma":[0.0004017217,0.0006847468,0.0003132911,0.00002283591,0.000009985556,0.0005824909,0.000353164,0.03900933,0.9160878,0.003894444,0.03802273,0.0006174791],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04648139,0.00007499557,0.9473659,0.00008298689,0.001641771,0.0003778246,0.000007829966,0.00306422,0.0009031009],"genre_scores_gemma":[0.9910409,0.000005001153,0.007674574,0.0001800699,0.0001435073,0.0006374322,0.000003097677,0.00002811659,0.000287335],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9445595,"threshold_uncertainty_score":0.8250558,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02015355805504851,"score_gpt":0.2696349021112425,"score_spread":0.249481344056194,"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."}}