k-Nearest neighbor query processing algorithm for cloaking regions towards user privacy protection in location-based services

  • Authors:

  • Jung-Ho Um;Yong-Ki Kim;Hyun-Jo Lee;Miyoung Jang;Jae-Woo Chang

  • Affiliations:

  • Korea Institute of Science and Technology Information, 245 Daehangno, Yuseong-gu, Daejeon 305-806, South Korea;Korea Institute of Science and Technology Information, 245 Daehangno, Yuseong-gu, Daejeon 305-806, South Korea;Dept. of Computer Engineering, Chonbuk National University, Jeonju, Chonbuk 561-756, South Korea;Dept. of Computer Engineering, Chonbuk National University, Jeonju, Chonbuk 561-756, South Korea;Dept. of Computer Engineering, Chonbuk National University, Jeonju, Chonbuk 561-756, South Korea

  • Venue:
  • Journal of Systems Architecture: the EUROMICRO Journal
  • Year:
  • 2012

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Abstract

Due to the advancement of wireless internet and mobile positioning technology, the application of location-based services (LBSs) has become popular for mobile users. Since users have to send their exact locations to obtain the service, it may lead to several privacy threats. To solve this problem, a cloaking method has been proposed to blur users' exact locations into a cloaked spatial region with a required privacy threshold (k). With the cloaked region, an LBS server can carry out a k-nearest neighbor (k-NN) search algorithm. Some recent studies have proposed methods to search k-nearest POIs while protecting a user's privacy. However, they have at least one major problem, such as inefficiency on query processing or low precision of retrieved result. To resolve these problems, in this paper, we propose a novel k-NN query processing algorithm for a cloaking region to satisfy both requirements of fast query processing time and high precision of the retrieved result. To achieve fast query processing time, we propose a new pruning technique based on a 2D-coodinate scheme. In addition, we make use of a Voronoi diagram for retrieving the nearest POIs efficiently. To satisfy the requirement of high precision of the retrieved result, we guarantee that our k-NN query processing algorithm always contains the exact set of k nearest neighbors. Our performance analysis shows that our algorithm achieves better performance in terms of query processing time and the number of candidate POIs compared with other algorithms.