Android malware detection method based on function call graphs

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Abstract

With the rapid development of mobile Internet, mobile devices have been widely used in people’s daily life, which has made mobile platforms a prime target for malware attack. In this paper we study on Android malware detection method. We propose the method how to extract the structural features of android application from its function call graph, and then use the structure features to build classifier to classify malware. The experiment results show that structural features can effectively improve the performance of malware detection methods.

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APA

Ding, Y., Zhu, S., & Xia, X. (2016). Android malware detection method based on function call graphs. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9950 LNCS, pp. 70–77). Springer Verlag. https://doi.org/10.1007/978-3-319-46681-1_9

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