Protecting location privacy and query privacy: a combined clustering approach. (10th March 2014)

• Record Type: Journal Article
• Authors: Lin, Chi; Wu, Guowei; Yu, Chang Wu; Xiang, Yang; Al‐Dubi, Ahmed; Liu, Lei; Chu, Xiaowen
• Is Part Of: Concurrency and computation. Volume 27:Number 12(2015:Aug.)
• Page Start: 3021
• Page End: 3043
• Publication Date: 2014-03-10
• Subjects: Parallel processing (Electronic computers) -- Periodicals; Parallel computers -- Periodicals; 004.35
• DOI: 10.1002/cpe.3244
• Languages: English
• ISSNs: 1532-0626

Abstract

<abstract abstract-type="main" id="cpe3244-abs-0001"> <title>Summary</title> <p id="cpe3244-para-0001">In this paper, a combined clustering algorithm namely <italic>enhanced clustering cloak</italic> (ECC), for protecting location privacy and query privacy is proposed. An iterative K‐means clustering method is developed to group the user requests into clusters for providing location safety. Meanwhile, a hierarchical clustering method for preserving the query privacy is used when creating clusters. <italic>ECC</italic> provides users with desirable spatial and temporal tolerances. It can defend sampling attacks, homogeneity attacks, and query association attacks simultaneously. Simulation results present that the <italic>ECC</italic> algorithm not only has merits in smaller number of clusters, shorter cloaking time, higher entropy and QoS level but also preserves location privacy and query privacy in continuous location based services. Copyright © 2014 John Wiley &amp; Sons, Ltd.</p> </abstract>