Abstract
In order to solve the problem that Android platform's sand-box mechanism prevents security protection software from accessing effective information to detect malware, this paper proposes a malicious software detection method based on power consumption. Firstly, the mobile battery consumption status information was obtained, and the Gaussian mixture model (GMM) was built by using Mel frequency cepstral coefficients (MFCC). Then, the GMM was used to analyze power consumption; malicious software can be classified and detected through classification processing. Experiment results demonstrate that the function of an application and its power consumption have a close relationship, and our method can detect some typical malicious application software accurately.
Cite
CITATION STYLE
Yang, H., & Tang, R. (2016). Power Consumption Based Android Malware Detection. Journal of Electrical and Computer Engineering, 2016. https://doi.org/10.1155/2016/6860217
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