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Article
On locating malicious code in piggybacked Android apps
Journal of Computer Science and Technology
  • Li LI, University of Luxembourg
  • Daoyuan LI, University of Luxembourg
  • Tegawende F. BISSYANDE, University of Luxembourg
  • Jacques KLEIN, University of Luxembourg
  • Haipeng CAI, Washington State University
  • David LO, Singapore Management University
  • Yves LE TRAON, University of Luxembourg
Publication Type
Journal Article
Version
acceptedVersion
Publication Date
11-2017
Abstract

To devise efficient approaches and tools for detecting malicious packages in the Android ecosystem, researchers are increasingly required to have a deep understanding of malware. There is thus a need to provide a framework for dissecting malware and locating malicious program fragments within app code in order to build a comprehensive dataset of malicious samples. Towards addressing this need, we propose in this work a tool-based approach called HookRanker, which provides ranked lists of potentially malicious packages based on the way malware behaviour code is triggered. With experiments on a ground truth of piggybacked apps, we are able to automatically locate the malicious packages from piggybacked Android apps with an accuracy@5 of 83.6% for such packages that are triggered through method invocations and an accuracy@5 of 82.2% for such packages that are triggered independently.

Keywords
  • Android,
  • piggybacked app,
  • malicious code,
  • HookRanker
Identifier
10.1007/s11390-017-1786-z
Publisher
Springer Verlag (Germany)
Copyright Owner and License
Authors
Creative Commons License
Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International
Additional URL
https://doi.org/10.1007/s11390-017-1786-z
Citation Information
Li LI, Daoyuan LI, Tegawende F. BISSYANDE, Jacques KLEIN, et al.. "On locating malicious code in piggybacked Android apps" Journal of Computer Science and Technology Vol. 32 Iss. 6 (2017) p. 1108 - 1124 ISSN: 1000-9000
Available at: http://works.bepress.com/david_lo/299/