Zeliang Kan, Haoyu Wang, Lei Wu, Yao Guo, Guoai Xu
{"title":"Deobfuscating Android Native Binary Code","authors":"Zeliang Kan, Haoyu Wang, Lei Wu, Yao Guo, Guoai Xu","doi":"10.1109/ICSE-Companion.2019.00135","DOIUrl":null,"url":null,"abstract":"In this paper, we propose an automated approach to facilitate the deobfuscation of Android native binary code. Specifically, given a native binary obfuscated by Obfuscator-LLVM (the most popular native code obfuscator), our deobfuscation system is capable of recovering the original Control Flow Graph. To the best of our knowledge, it is the first work that aims to tackle the problem. We have applied our system in different scenarios, and the experimental results demonstrate the effectiveness of our system based on generic similarity comparison metrics.","PeriodicalId":273100,"journal":{"name":"2019 IEEE/ACM 41st International Conference on Software Engineering: Companion Proceedings (ICSE-Companion)","volume":"253 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-05-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"10","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 IEEE/ACM 41st International Conference on Software Engineering: Companion Proceedings (ICSE-Companion)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICSE-Companion.2019.00135","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 10
Abstract
In this paper, we propose an automated approach to facilitate the deobfuscation of Android native binary code. Specifically, given a native binary obfuscated by Obfuscator-LLVM (the most popular native code obfuscator), our deobfuscation system is capable of recovering the original Control Flow Graph. To the best of our knowledge, it is the first work that aims to tackle the problem. We have applied our system in different scenarios, and the experimental results demonstrate the effectiveness of our system based on generic similarity comparison metrics.