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Using G Features to Improve the Efficiency of Function Call Graph Based Android Malware Detection

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Abstract

In this paper, we proposed a G features based Android malware detecting scheme with information of Function Call Graph. The experimental results showed that our G features based detecting scheme obtained a high detecting performance in up-to-date malware testing dataset. Besides, the collapsing issue induced by the high-dimension vectors of traditional Function Call Graph detection can also be avoided with our methods.

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Acknowledgements

National Natural Science Foundation of China (Grant Nos. 61373102, 61771338).

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Authors and Affiliations

  1. School of Microelectronics, Tianjin University, Tianjin, 300072, China

    Yu Liu & Liqiang Zhang

  2. School of Electrical and Information Engineering, Tianjin University, Tianjin, 300072, China

    Xiangdong Huang

Authors
  1. Yu Liu
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  2. Liqiang Zhang
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  3. Xiangdong Huang
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Correspondence to Xiangdong Huang.

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Liu, Y., Zhang, L. & Huang, X. Using G Features to Improve the Efficiency of Function Call Graph Based Android Malware Detection. Wireless Pers Commun 103, 2947–2955 (2018). https://doi.org/10.1007/s11277-018-5982-0

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