Smartphone usage has been continuously increasing in recent years. In addition, Android devices are widely used in our daily life, becoming the most attractive target for hackers. Therefore, malware analysis of Android platform is in urgent demand. Static analysis and dynamic analysis methods are two classical approaches. However, they also have some drawbacks. Motivated by this, we present Demadroid, a framework to implement the detection of Android malware. We obtain the dynamic information to build Object Reference Graph and propose -VF2 algorithm for graph matching. Extensive experiments show that Demadroid can efficiently identify the malicious features of malware. Furthermore, the system can effectively resist obfuscated attacks and the variants of known malware to meet the demand for actual use.
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