• DocumentCode
    3722533
  • Title

    Detecting Malware for Android Platform: An SVM-Based Approach

  • Author

    Wenjia Li;Jigang Ge;Guqian Dai

  • Author_Institution
    Dept. of Comput. Sci., New York Inst. of Technol., New York, NY, USA
  • fYear
    2015
  • Firstpage
    464
  • Lastpage
    469
  • Abstract
    In recent years, Android has become one of the most popular mobile operating systems because of numerous mobile applications (apps) it provides. However, the malicious Android applications (malware) downloaded from third-party markets have significantly threatened users´ security and privacy, and most of them remain undetected due to the lack of efficient and accurate malware detection techniques. In this paper, we study a malware detection scheme for Android platform using an SVM-based approach, which integrates both risky permission combinations and vulnerable API calls and use them as features in the SVM algorithm. To validate the performance of the proposed approach, extensive experiments have been conducted, which show that the proposed malware detection scheme is able to identify malicious Android applications effectively and efficiently.
  • Keywords
    "Androids","Humanoid robots","Malware","Smart phones","Feature extraction","Mobile communication"
  • Publisher
    ieee
  • Conference_Titel
    Cyber Security and Cloud Computing (CSCloud), 2015 IEEE 2nd International Conference on
  • Type

    conf

  • DOI
    10.1109/CSCloud.2015.50
  • Filename
    7371523