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A Framework for Evaluating Mobile App Repackaging Detection Algorithms

2013; Springer Science+Business Media; Linguagem: Inglês

10.1007/978-3-642-38908-5_13

1611-3349

Heqing Huang, Sencun Zhu, Peng Liu, Dinghao Wu,

Web Data Mining and Analysis

Because it is not hard to reverse engineer the Dalvik bytecode used in the Dalvik virtual machine, Android application repackaging has become a serious problem. With repackaging, a plagiarist can simply steal others' code violating the intellectual property of the developers. More seriously, after repackaging, popular apps can become the carriers of malware, adware or spy-ware for wide spreading. To maintain a healthy app market, several detection algorithms have been proposed recently, which can catch some types of repackaged apps in various markets efficiently. However, they are generally lack of valid analysis on their effectiveness. After analyzing these approaches, we find simple obfuscation techniques can potentially cause false negatives, because they change the main characteristics or features of the apps that are used for similarity detections. In practice, more sophisticated obfuscation techniques can be adopted (or have already been performed) in the context of mobile apps. We envision this obfuscation based repackaging will become a phenomenon due to the arms race between repackaging and its detection. To this end, we propose a framework to evaluate the obfuscation resilience of repackaging detection algorithms comprehensively. Our evaluation framework is able to perform a set of obfuscation algorithms in various forms on the Dalvik bytecode. Our results provide insights to help gauge both broadness and depth of algorithms' obfuscation resilience. We applied our framework to conduct a comprehensive case study on AndroGuard, an Android repackaging detector proposed in Black-hat 2011. Our experimental results have demonstrated the effectiveness and stability of our framework.