一句话：系统研究 Android 应用 UI 混淆，设计 9 种方法并揭示其使自动化 UI 分析工具性能严重下降。
Android 应用的 UI 驱动特性推动了自动化 UI 分析在应用分析、恶意应用检测和应用测试中的应用，但这类方法面对日益普及的应用保护技术时是否仍然有效尚不明确。本文首次系统研究 Android 应用的 UI 混淆及其影响：指出已有自动化 UI 分析方法的弱点，设计 9 种 UI 混淆方案，并克服若干技术挑战实现工具 UIObfuscator。随后用 UIObfuscator 保护的应用测试 3 类依赖自动化 UI 分析的工具，发现其性能严重下降。工作揭示了自动化 UI 分析的局限，也为应用保护技术提供启示。
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.
@inproceedings{paperbot6026,
title = {UI obfuscation and its effects on automated UI analysis for Android apps},
author = {Hao Zhou and Ting Chen and Haoyu Wang and Le Yu and Xiapu Luo and Ting Wang and Wei Zhang},
booktitle = {ASE},
year = {2020},
doi = {10.1145/3324884.3416642}
}