Abstract
Recently, Android malware is spreading rapidly. Although static or dynamic analysis techniques for detecting Android malware can provide a comprehensive view, it is still subjected to time consuming and high cost in deployment and manual efforts. In this paper, we propose A3, an Automatic Analysis of Android malware, to detect Android malware automatically. Unlike traditional reverse-engineering methods, A3 looks for Command & Control (C&C) Server), monitors the sensitive API invoking, and declares Intent-filter automatically. Then it constructs the relationship graph of the function calls and key contexts or paths for detecting Android malware. The experimental results show that A3 can do an effective automatic analysis for Android malware and has a good performance.
Cite
CITATION STYLE
Luoshi, Z., Yan, N., Xiao, W., Zhaoguo, W., & Yibo, X. (2013). A3: Automatic Analysis of Android Malware. In Proceedings of the The 1st International Workshop on Cloud Computing and Information Security (Vol. 52). Atlantis Press. https://doi.org/10.2991/ccis-13.2013.22
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