A Hierarchical Clustering-Based Spatial Cloaking Algorithm for Location-Based Services

Abstract

The rapid growth of smart phones has made location-based services (LBS) widely available. LBS can be used to enhance "Homeland Security." Since the use of LBS can raise privacy issues, users want to prevent government agencies from tracking their locations. To avoid such a situation, some kind of location privacy mechanism should be provided. Most of the studies for location privacy try to preserve location privacy by achieving what is known as location K-anonymity. However, location K-anonymity can be compromised even when there are always more than K users in the anonymizing spatial regions (ASR). A reciprocity property is introduced as a sufficient condition for location K-anonymity. In this paper, we propose a hierarchical clustering-based spatial cloaking algorithm for LBS. Our spatial cloaking algorithm satisfies the reciprocity property. The experimental results show, in terms of the ASR size, that the proposed algorithm is better than Hilbert Cloak and comparable to RC-AR. In terms of the ASR generation time, the proposed algorithm is much better in its performance than RC-AR and similar in performance to Hilbert Cloak.