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Android Malware Detection Method Based on Function Call Graphs

  • Yuxin DingEmail author
  • Siyi Zhu
  • Xiaoling Xia
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9950)

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.

Keywords

Android malware Static detection Machine learning 

Notes

Acknowledgment

This work was partially supported by Scientific Research Foundation in Shenzhen (Grant No. JCYJ20140627163809422, JCYJ20160525163756635), Guangdong Natural Science Foundation (Grant No. 2016A030313664) and Key Laboratory of Network Oriented Intelligent Computation (Shenzhen).

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Copyright information

© Springer International Publishing AG 2016

Authors and Affiliations

  1. 1.Key Laboratory of Network Oriented Intelligent Computation, Department of Computer Sciences and TechnologyHarbin Institute of Technology Shenzhen Graduate SchoolShenzhenChina

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