{"id":"W4312300465","doi":"10.1145/3524489.3527300","title":"A survey of security vulnerabilities in Android automotive apps","year":2022,"lang":"en","type":"article","venue":"","topic":"Advanced Malware Detection Techniques","field":"Computer Science","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Android (operating system); Computer science; Automotive industry; Android application; Computer security; Android app; Permission; Operating system; Engineering","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00134106,0.0004616595,0.0003246066,0.00441097,0.0006713876,0.0008592641,0.0004029211,0.0006177633,0.0008733448],"category_scores_gemma":[0.008991812,0.0003132017,0.0004939549,0.002059825,0.0005128178,0.002133538,0.0008213327,0.0005216366,0.0003679849],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003568977,"about_ca_system_score_gemma":0.0006497481,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002586766,"about_ca_topic_score_gemma":0.003501718,"domain_scores_codex":[0.9971155,0.0004503462,0.0003708968,0.0004260385,0.001428219,0.000209081],"domain_scores_gemma":[0.9873214,0.007156372,0.002367626,0.0006657789,0.002217159,0.0002715935],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0005356086,0.0002671408,0.5543928,0.004507885,0.0002717615,0.003960236,0.01090943,0.002413896,0.03383851,0.003090761,0.008931012,0.376881],"study_design_scores_gemma":[0.00001818826,0.001123261,0.8309801,0.002432213,0.0005969484,0.03071775,0.01016185,0.00740799,0.02851171,0.002048502,0.08580706,0.0001945589],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9675501,0.01783145,0.004407382,0.0006492701,0.00006029632,0.0001782521,0.001547381,0.0004928989,0.007282953],"genre_scores_gemma":[0.9828277,0.009558442,0.003784147,0.0002909118,0.00003216093,0.00008362351,0.001615186,0.00008932265,0.00171861],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00441097,"threshold_uncertainty_score":0.007092297,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0156072528818202,"score_gpt":0.2623371265219911,"score_spread":0.2467298736401709,"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."}}