Publication Type
Conference Proceeding Article
Version
publishedVersion
Publication Date
7-2015
Abstract
To support intensive computations on resource-restricting mobile devices, studies have been made to enable the offloading of a part of a mobile program to the cloud. However, none of the existing approaches considers user privacy when transmitting code and data off the device, resulting in potential privacy breach. In this paper, we present the design and implementation of a system that automatically performs fine-grained privacy-preserving Android app offloading. It utilizes static analysis and bytecode instrumentation techniques to ensure transparent and efficient Android app offloading while preserving user privacy. We evaluate the effectiveness and performance of our system using two Android apps. Preliminary experimental results show that our offloading technique can effectively preserve user privacy while reducing hardware resource consumption at the same time.
Keywords
Android apps, Bytecode instrumentation, Design and implementations, Fine grained, Hardware resources, Privacy breaches, Privacy preserving, Public clouds
Discipline
Information Security
Research Areas
Cybersecurity; Information Systems and Management
Publication
Proceedings of the 7th USENIX Workshop on Hot Topics in Cloud Computing, California, USA, 2015 July 6-7
City or Country
US
Citation
DUAN, Yue; ZHANG, Mu; YIN, Heng; and TANG, Yuzhe.
Privacy-preserving offloading of mobile app to the public cloud. (2015). Proceedings of the 7th USENIX Workshop on Hot Topics in Cloud Computing, California, USA, 2015 July 6-7.
Available at: https://ink.library.smu.edu.sg/sis_research/8175
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.