X-Region: A framework for location privacy preservation in mobile peer-to-peer networks

While enjoying various LBS location-based services, users also face the threats of location privacy disclosure. This is because even if the communications between users and LBS providers can be encrypted and anonymized, the sensitive information inside LBS queries may disclose the exact location or even the identity of a user. The existing research on location privacy preservation in mobile peer-to-peer P2P networks assumed that users trust each other and directly share location information with each other. Nonetheless, this assumption is not practical for most of the mobile P2P scenarios, for example, an adversary can pretend to be a normal user and collect the locations of other users. Aiming at this issue, this paper presents x-region as a solution to preserve the location privacy in a mobile P2P environment where no trust relationships are assumed amongst mobile users. The main idea is to allow users to share a blurred region known as x-region instead of their exact locations so that one cannot distinguish any user from others inside the region. We propose a theoretical metric for measuring the anonymity property of x-region, together with three algorithms for generating an x-region, namely, benchmark algorithm, weighted expanding algorithm, and aggressive weighted expanding algorithm. These algorithms achieve the anonymity and QoS requirements with different strategies. Our experiments verify the performance of the algorithms against three key metrics. Copyright © 2013 John Wiley & Sons, Ltd.