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A survey on dynamic mobile malware detection

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Abstract

The outstanding advances of mobile devices stimulate their wide usage. Since mobile devices are coupled with third-party applications, lots of security and privacy problems are induced. However, current mobile malware detection and analysis technologies are still imperfect, ineffective, and incomprehensive. Due to the specific characteristics of mobile devices such as limited resources, constant network connectivity, user activities and location sensing, and local communication capability, mobile malware detection faces new challenges, especially on dynamic runtime malware detection. Many intrusions or attacks could happen after a mobile app is installed or executed. The literature still expects practical and effective dynamic malware detection approaches. In this paper, we give a thorough survey on dynamic mobile malware detection. We first introduce the definition, evolution, classification, and security threats of mobile malware. Then, we summarize a number of criteria and performance evaluation measures of mobile malware detection. Furthermore, we compare, analyze, and comment on existing mobile malware detection methods proposed in recent years based on evaluation criteria and measures. Finally, we figure out open issues in this research field and motivate future research directions.

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Acknowledgment

This work is sponsored by the National Key Research and Development Program of China (grant 2016YFB0800704), the NSFC (grants 61672410 and U1536202), the Project Supported by Natural Science Basic Research Plan in Shaanxi Province of China (Program No. 2016ZDJC-06), the 111 project (grants B16037 and B08038), the PhD grant of the Chinese Educational Ministry (grant JY0300130104), and Aalto University.

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  1. The State Key Laboratory on Integrated Services Networks, School of Cyber Engineering, Xidian University, Xi’an, 710071, China

    Ping Yan & Zheng Yan

  2. Department of Communications and Networking, Aalto University, 02150, Espoo, Finland

    Zheng Yan

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  1. Ping Yan
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  2. Zheng Yan
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Correspondence to Zheng Yan.

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Yan, P., Yan, Z. A survey on dynamic mobile malware detection. Software Qual J 26, 891–919 (2018). https://doi.org/10.1007/s11219-017-9368-4

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