On locating malicious code in piggybacked Android apps

• Main Authors: LI, Li, LI, Daoyuan, BISSYANDE, Tegawende F., KLEIN, Jacques, CAI, Haipeng, LO, David, LE TRAON, Yves
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2017
• Subjects: Android; piggybacked app; malicious code; HookRanker; Programming Languages and Compilers; Software Engineering
• Online Access: https://ink.library.smu.edu.sg/sis_research/3914; https://ink.library.smu.edu.sg/context/sis_research/article/4916/viewcontent/101007_2Fs11390_017_1786_z.pdf
• Institution: Singapore Management University

To devise efficient approaches and tools for detecting malicious packages in the Android ecosystem, researchers are increasingly required to have a deep understanding of malware. There is thus a need to provide a framework for dissecting malware and locating malicious program fragments within app code in order to build a comprehensive dataset of malicious samples. Towards addressing this need, we propose in this work a tool-based approach called HookRanker, which provides ranked lists of potentially malicious packages based on the way malware behaviour code is triggered. With experiments on a ground truth of piggybacked apps, we are able to automatically locate the malicious packages from piggybacked Android apps with an accuracy@5 of 83.6% for such packages that are triggered through method invocations and an accuracy@5 of 82.2% for such packages that are triggered independently.