IDEAS home Printed from https://ideas.repec.org/a/igg/jcac00/v11y2021i4p113-135.html
   My bibliography  Save this article

Android Malware Detection Techniques in Traditional and Cloud Computing Platforms: A State-of-the-Art Survey

Author

Listed:
  • Aayush Vishnoi

    (Graphic Era University (Deemed), Dehradun, India)

  • Preeti Mishra

    (Dept. of CSE, Graphic Era University (Deemed), India & Dept. of CS, Doon University Dehradun, India)

  • Charu Negi

    (Graphic Era Hill University, Dehradun, India)

  • Sateesh Kumar Peddoju

    (Indian Institute of Technology, Roorkee, India)

Abstract

In the mobile world, Android is the most popular choice of manufacturers and users alike. Meanwhile, a number of malicious applications abbreviated as malapps or malware have increased explosively. Malware writers make use of existing apps to send malware to users' devices. To check presence of malware, the authors perform malware analysis of apps. In this paper, they provide a comprehensive review on state-of-the-art android malware detection approaches using traditional and cloud computing platforms. The paper also presents attack taxonomy to better understand security threat against Android. Furthermore, it describes various possible attacking features (static and dynamic) and their analysis mechanism. Various security tools have also been discussed. It presents two case studies: one for malware feature extraction and the other for demonstrating the use of machine learning for malware analysis in order to provide a practical insight of malware analysis. The results of malware analysis seem to be promising.

Suggested Citation

  • Aayush Vishnoi & Preeti Mishra & Charu Negi & Sateesh Kumar Peddoju, 2021. "Android Malware Detection Techniques in Traditional and Cloud Computing Platforms: A State-of-the-Art Survey," International Journal of Cloud Applications and Computing (IJCAC), IGI Global, vol. 11(4), pages 113-135, October.
  • Handle: RePEc:igg:jcac00:v:11:y:2021:i:4:p:113-135
    as

    Download full text from publisher

    File URL: http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/IJCAC.2021100107
    Download Restriction: no
    ---><---

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:igg:jcac00:v:11:y:2021:i:4:p:113-135. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Journal Editor (email available below). General contact details of provider: https://www.igi-global.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.