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A New Spatial Transformation Scheme for Preventing Location Data Disclosure in Cloud Computing

A New Spatial Transformation Scheme for Preventing Location Data Disclosure in Cloud Computing
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Author(s): Min Yoon (Chonbuk National University, South Korea), Hyeong-il Kim (Chonbuk National University, South Korea), Miyoung Jang (Chonbuk National University, South Korea) and Jae-Woo Chang (Chonbuk National University, South Korea)
Copyright: 2016
Pages: 25
Source title: Geospatial Research: Concepts, Methodologies, Tools, and Applications
Source Author(s)/Editor(s): Information Resources Management Association (USA)
DOI: 10.4018/978-1-4666-9845-1.ch084

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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 chapter, 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.

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