Document Type
Conference Proceeding
Language
eng
Format of Original
9 p.
Publication Date
7-2010
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Source Publication
Proceedings of the 34th Annual International Computer Software and Applications Conference
Source ISSN
9780769540856
Original Item ID
DOI: 10.1109/COMPSAC.2010.14
Abstract
The challenge of preserving user’s location privacy is more important now than ever before with the proliferation of handheld devices and the pervasive use of location based services. To protect location privacy, we must ensure k-anonymity so that the user remains indistinguishable among k-1 other users. There is no better way but to use a location anonymizer (LA) to achieve k-anonymity. However, its knowledge of each user’s current location makes it susceptible to be a single-point-of-failure. In this paper, we propose a formal location privacy framework, termed SafeGrid that can work with or without an LA. In SafeGrid, LA is designed in such a way that it is no longer a single point of failure. In addition, it is resistant to known attacks and most significantly, the cloaking algorithm it employs meets reciprocity condition. Simulation results exhibit its better performance in query processing and cloaking region calculation compared with existing solutions. As an added feature, in SafeGrid a user has the option of not using LA, yet achieving as much obfuscation (deliberate degradation of location data) as needed without ever sacrificing performance gain.
Recommended Citation
Ahamed, Sheikh Iqbal and Chowdhury, S. Hasan, "An Approach for Ensuring Robust Safeguard against Location Privacy Violation" (2010). Mathematics, Statistics and Computer Science Faculty Research and Publications. 412.
https://epublications.marquette.edu/mscs_fac/412
Comments
Accepted version. Published as part of the proceedings of the conference, 34th Annual International Computer Software and Applications Conference, 2010: 82-91. DOI.
© 2010 IEEE. Reprinted, with permission, from Abir K Bekhet and Jaclene A Zauszniewski, Methodological Triangulation: an Approach to Understanding Data, 34th Annual International Computer Software and Applications Conference, and July 2010.
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