Linear Function Based Transformation Scheme for Preserving Database Privacy in Cloud Computing

Abstract

Because much interest in spatial database in cloud computing has been attracted, studies on preserving location data privacy in cloud computing have been actively done. However, since the existing spatial transformation schemes are weak to proximity attack, they cannot preserve the privacy of users who enjoy location-based services from the cloud computing. Therefore, a transformation scheme for providing a safe service to users is required. So, we, in this paper, propose a new transformation scheme based on a line symmetric transformation (LST). The proposed scheme performs both LST-based data distribution and error injection transformation for preventing 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.