UI obfuscation and its effects on automated UI analysis for Android apps

Abstract

The UI driven nature of Android apps has motivated the development of automated UI analysis for various purposes, such as app analysis, malicious app detection, and app testing. Although existing automated UI analysis methods have demonstrated their capability in dissecting apps' UI, little is known about their effectiveness in the face of app protection techniques, which have been adopted by more and more apps. In this paper, we take a first step to systematically investigate UI obfuscation for Android apps and its effects on automated UI analysis. In particular, we point out the weaknesses in existing automated UI analysis methods and design 9 UI obfuscation approaches. We implement these approaches in a new tool named UIObfuscator after tackling several technical challenges. Moreover, we feed 3 kinds of tools that rely on automated UI analysis with the apps protected by UIObfuscator, and find that their performances severely drop. This work reveals limitations of automated UI analysis and sheds light on app protection techniques.