A Cloud-Assisted Malware Detection Framework for Mobile Devices

Shih Hao Hung, Chia Heng Tu, Chi Wei Yeh

研究成果: Conference contribution

4 引文 斯高帕斯(Scopus)


While mobile applications make our lives more convenient, security concerns may arise when the mobile applications contain malicious code that would harm the mobile devices and their users financially and physically. In this article, we propose a malware detection framework to protect the mobile devices with the help of the cloud, where the cloud is equipped with the facilities for automatic analysis of large amount of new malware generated everyday, and the device is able to detect malicious intents of running software in real-time based on the knowledge of the analyzed malware. We evaluate the performance of our framework with Android-based systems as case studies. In particular, we study the impact of different system configurations on the time required for malware detection, including detecting algorithms (i.e., CNN and SVM), mobile processors (i.e., ARM CPU and NVIDIA GPU), and wireless networks (i.e., Wi-Fi and 3G for the communication between the device and the cloud). To the best of our knowledge, we are not aware of any other work studying performance impacts of the system configurations of the malware detection systems using the physical machines. As the widespread of malware, we believe that our empirical study is useful when designing antivirus software and can be applied to different application domains, such as automotive, and smart home.

主出版物標題Proceedings - 2016 International Computer Symposium, ICS 2016
發行者Institute of Electrical and Electronics Engineers Inc.
出版狀態Published - 2017 二月 16
事件2016 International Computer Symposium, ICS 2016 - Chiayi, Taiwan
持續時間: 2016 十二月 152016 十二月 17


名字Proceedings - 2016 International Computer Symposium, ICS 2016


Other2016 International Computer Symposium, ICS 2016

All Science Journal Classification (ASJC) codes

  • 電腦視覺和模式識別
  • 硬體和架構
  • 電腦網路與通信
  • 電腦科學應用


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