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

Min Yoon, Hyeong-il Kim, Miyoung Jang, Jae-Woo Chang
Copyright: © 2016 |Pages: 25
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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Introduction

Due to the recent developments of wireless positioning capabilities, such as GPS-equipped smart phones and PDA, location-based services (LBSs) are popular (Taniar, 2011; Safar, 2009; Xuan, 2011). In LBSs, mobile users are usually getting location information combined with traffic information, friend finder, and adjacent neighbor. However, the users can make use of these kinds of services by revealing their exact location to a location-based service provider. So, the users may meet a privacy violation problem (Xiong, 2007). Recently, database outsourcing (Singh, 2008; Singh, 2009) has been one of the most popular trends in cloud computing. Due to the rapid advancements in LBSs, the speed of transmitting a terabyte of data over long distance has significantly increased and the amount of information generated in our daily lives has grown rapidly over the past decade. This large amount of information requires sophisticated management systems that are beyond the capabilities of individuals or small business. Thus, database outsourcing boosts up its popularity. Because database is separated from a data owner (DO) in database outsourcing, a service provider (SP) is responsible for data storage and performs query processing for the authorized query issuer. However, because the data owner does not want to disclose the original data to the service provider, privacy issues for the database outsourcing have been actively studied (Xiong, 2007; Qiu, 2008; Yi, 2009; Haber, 2009; Yang, 2009; Sachridis, 2010; Jiang, 2010; Ciriani, 2011; Zhou, 2012; Anil, 2013).

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