A New Spatial Transformation Scheme for Preventing Location Data Disclosure in Cloud Computing
Min Yoon,
Hyeong-il Kim,
Miyoung Jang and
Jae-Woo Chang
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Min Yoon: Department of Computer Engineering, Chonbuk National University, Jeonju, South Korea
Hyeong-il Kim: Department of Computer Engineering, Chonbuk National University, Jeonju, South Korea
Miyoung Jang: Department of Computer Engineering, Chonbuk National University, Jeonju, South Korea
Jae-Woo Chang: Department of Computer Engineering,Chonbuk National University,Jeonju, South Korea
International Journal of Data Warehousing and Mining (IJDWM), 2014, vol. 10, issue 4, 26-49
Abstract:
Because much interest in spatial database for cloud computing has been attracted, studies on preserving 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 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 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.
Date: 2014
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Persistent link: https://EconPapers.repec.org/RePEc:igg:jdwm00:v:10:y:2014:i:4:p:26-49
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