Automated Third-Party Library Detection for Android Applications: Are We There Yet?
Xian Zhan, Lingling Fan, Tianming Liu, Sen Chen, Li Li, Haoyu Wang, Yifei Xu, Xiapu Luo, Yang Liu
Abstract
Third-party libraries (TPLs) have become a significant part of the Android ecosystem. Developers can employ various TPLs with different functionalities to facilitate their app development. Unfortunately, the popularity of TPLs also brings new challenges and even threats. TPLs may carry malicious or vulnerable code, which can infect popular apps to pose threats to mobile users. Besides, the code of third-party libraries could constitute noises in some downstream tasks (e.g., malware and repackaged app detection). Thus, researchers have developed various tools to identify TPLs. However, no existing work has studied these TPL detection tools in detail; different tools focus on different applications with performance differences, but little is known about them. To better understand existing TPL detection tools and dissect TPL detection techniques, we conduct a comprehensive empirical study to fill the gap by evaluating and comparing all publicly available TPL detection tools based on four criteria: effectiveness, efficiency, code obfuscation-resilience capability, and ease of use. We reveal their advantages and disadvantages based on a systematic and thorough empirical study. Furthermore, we also conduct a user study to evaluate the usability of each tool. The results show
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