Shikra: A Behavior-Based Android Malware Detection Framework
Zhaohui Ma, Zi-hao Chen, Xinming Wang, Ruihua Nie, Gansen Zhao, Jie-chao Wu, Xue-qi Ren · 2017
With the growth of Android platform malicious application, the seperation of malicious application from nonmalicious application has become challenging. In recent years, a combination of static analysis and dynamic analysis of the idea is very popular. However, it is very costly for dynamic analysis to achieve high coverage. In this article we present an efficient, lightweight and behavior-based architecture based on the behavior of malicious developers. Information and behavior preferences of malicious developers in binary code are collected. And through the multi-plane SVM Android application malicious and non-malicious division.