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Protecting location privacy and query privacy: a combined clustering approach.

Authors :
Lin, Chi
Wu, Guowei
Yu, Chang Wu
Source :
Concurrency & Computation: Practice & Experience; Aug2015, Vol. 27 Issue 12, p3021-3043, 23p
Publication Year :
2015

Abstract

In this paper, a combined clustering algorithm namely enhanced clustering cloak (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. ECC 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 ECC 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 & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
15320626
Volume :
27
Issue :
12
Database :
Complementary Index
Journal :
Concurrency & Computation: Practice & Experience
Publication Type :
Academic Journal
Accession number :
108562548
Full Text :
https://doi.org/10.1002/cpe.3244