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Protecting location privacy and query privacy: a combined clustering approach
Author(s) -
Lin Chi,
Wu Guowei,
Yu Chang Wu
Publication year - 2014
Publication title -
concurrency and computation: practice and experience
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.309
H-Index - 67
eISSN - 1532-0634
pISSN - 1532-0626
DOI - 10.1002/cpe.3244
Subject(s) - computer science , cloaking , cluster analysis , data mining , privacy protection , information privacy , location based service , entropy (arrow of time) , information retrieval , computer security , computer network , artificial intelligence , physics , metamaterial , optoelectronics , quantum mechanics
Summary 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.