Publication Type
Journal Article
Version
publishedVersion
Publication Date
6-2017
Abstract
The Android packaging model offers ample opportunities for malware writers to piggyback malicious code in popular apps, which can then be easily spread to a large user base. Although recent research has produced approaches and tools to identify piggybacked apps, the literature lacks a comprehensive investigation into such phenomenon. We fill this gap by: 1) systematically building a large set of piggybacked and benign apps pairs, which we release to the community; 2) empirically studying the characteristics of malicious piggybacked apps in comparison with their benign counterparts; and 3) providing insights on piggybacking processes. Among several findings providing insights analysis techniques should build upon to improve the overall detection and classification accuracy of piggybacked apps, we show that piggybacking operations not only concern app code, but also extensively manipulates app resource files, largely contradicting common beliefs. We also find that piggybacking is done with little sophistication, in many cases automatically, and often via library code.
Keywords
android malware, Android security, code grafting, piggybacking attack
Discipline
Information Security | Software Engineering
Research Areas
Software and Cyber-Physical Systems
Publication
IEEE Transactions on Information Forensics and Security
Volume
12
Issue
6
First Page
1269
Last Page
1284
ISSN
1556-6013
Identifier
10.1109/TIFS.2017.2656460
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Citation
LI, Li; LI, Daoyuan; BISSYANDE, Tegawende F.; KLEIN, Jacques; TRAON, Yves Le; LO, David; and CAVALLARO, Lorenzo.
Understanding Android app piggybacking: A systematic study of malicious code grafting. (2017). IEEE Transactions on Information Forensics and Security. 12, (6), 1269-1284.
Available at: https://ink.library.smu.edu.sg/sis_research/3694
Copyright Owner and License
Authors
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Additional URL
https://doi.org/10.1109/TIFS.2017.2656460