Abstract
Because much interest in spatial database for cloud computing has been attracted, studies on preserv-ing location data privacy have been actively done. However, since the existing spatial transformation schemes are weak to a proximity attack, they cannot preserve the privacy of users who enjoy location-based services in the cloud computing. Therefore, a transformation scheme is required for providing a safe service to users. We, in this chapter, propose a new transformation scheme based on a line sym-metric transformation (LST). The proposed scheme performs both LST-based data distribution and error injection transformation for preventing a proximity attack effectively. Finally, we show from our performance analysis that the proposed scheme greatly reduces the success rate of the proximity attack while performing the spatial transformation in an efficient way.
| Original language | English |
|---|---|
| Title of host publication | Geospatial Research |
| Subtitle of host publication | Concepts, Methodologies, Tools, and Applications |
| Publisher | IGI Global |
| Pages | 1752-1776 |
| Number of pages | 25 |
| Volume | 3 |
| ISBN (Electronic) | 9781466698468 |
| ISBN (Print) | 9781466698451 |
| DOIs | |
| State | Published - 2016.01.1 |
Fingerprint
Dive into the research topics of 'A New Spatial Transformation Scheme for Preventing Location Data Disclosure in Cloud Computing'. Together they form a unique fingerprint.Cite this
- APA
- Author
- BIBTEX
- Harvard
- Standard
- RIS
- Vancouver