Understanding Android Obfuscation Techniques: A Large-Scale Investigation in the Wild

• Published in: Security and Privacy in Communication Networks Vol. 254; pp. 172 - 192
• Main Authors: Dong, Shuaike, Li, Menghao, Diao, Wenrui, Liu, Xiangyu, Liu, Jian, Li, Zhou, Xu, Fenghao, Chen, Kai, Wang, XiaoFeng, Zhang, Kehuan
• Format: Book Chapter
• Language: English
• Published: Switzerland Springer International Publishing AG 2018; Springer International Publishing
• Series: Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
• Subjects: Android; Code protection; Obfuscation; Static analysis
• ISBN: 9783030017002; 3030017001
• ISSN: 1867-8211; 1867-822X
• DOI: 10.1007/978-3-030-01701-9_10

Program code is a valuable asset to its owner. Due to the easy-to-reverse nature of Java, code protection for Android apps is of particular importance. To this end, code obfuscation is widely utilized by both legitimate app developers and malware authors, which complicates the representation of source code or machine code in order to hinder the manual investigation and code analysis. Despite many previous studies focusing on the obfuscation techniques, however, our knowledge of how obfuscation is applied by real-world developers is still limited. In this paper, we seek to better understand Android obfuscation and depict a holistic view of the usage of obfuscation through a large-scale investigation in the wild. In particular, we focus on three popular obfuscation approaches: identifier renaming, string encryption and Java reflection. To obtain the meaningful statistical results, we designed efficient and lightweight detection models for each obfuscation technique and applied them to our massive APK datasets (collected from Google Play, multiple third-party markets, and malware databases). We have learned several interesting facts from the result. For example, more apps on third-party markets than malware use identifier renaming, and malware authors use string encryption more frequently. We are also interested in the explanation of each finding. Therefore we carry out in-depth code analysis on some Android apps after sampling. We believe our study will help developers select the most suitable obfuscation approach, and in the meantime help researchers improve code analysis systems in the right direction.