Protecting query privacy in location-based services

Abstract

The popularity of location-based services (LBSs) leads to severe concerns on users' privacy. With the fast growth of Internet applications such as online social networks, more user information becomes available to the attackers, which allows them to construct new contextual information. This gives rise to new challenges for user privacy protection and often requires improvements on the existing privacypreserving methods. In this paper, we classify contextual information related to LBS query privacy and focus on two types of contexts-user prof iles and query dependency: user profiles have not been deeply studied in LBS query privacy protection, while we are the first to show the impact of query dependency on users' query privacy. More specifically, we present a general framework to enable the attackers to compute a distribution on users with respect to issuing an observed request. The framework can model attackers with different contextual information. We take user profiles and query dependency as examples to illustrate the implementation of the framework and their impact on users' query privacy. Our framework subsequently allows us to show the insufficiency of existing query privacy metrics, e.g., k-anonymity, and propose several new metrics. In the end, we develop new generalisation algorithms to compute regions satisfying users' privacy requirements This article is a revised and extended version of our two conference papers [7,8].Xihui Chen is supported by an AFR PhD grant from the National Research Fund, Luxembourg.

Query-Dependency-Aware Location Privacy Protection for Road Networks

“…Damiani et al, [20] surveyed the effect of location sensitivity on the privacy degree of anonymous space and accordingly proposed a solution to sensitive location leak in location sharing application of social networks. Chen and Pang [1] classified background information obtained by attacker into static and dynamic classifications and emphatically analyzed the impact of user's static information including profiles and query dependency on user's privacy, and proposed a corresponding privacy protection method for query privacy protection.…”

“…It is assumed that current query issued by a user is only affected by his last query and the continuous queries are regarded as a Markov process [1,25], then the query dependency of the current query qj issued by user u with respect to his last query qi is denoted by depu(qi, qj) and can be obtained by the conditional probability pu(qj|qi) as…”

“…With the rapid developments of wireless communication technology, positioning technology, and mobile object database management technology, especially, as well as the rise of Internet of Things, location-based services (LBS) have being extended from the early application of quickly positioning patient in emergency to wider fields [1,2]. More and more users use smart phones or other mobile terminals to obtain personalized LBS by providing their current location information.…”

A Strand Space Approach to Provable Anonymity

“…Due to its subtle nature, anonymity has been the subject of many research paper. For instance, the proposed definitions aim to capture different aspects of anonymity (either possibilistic [1][2][3][4][5] or probabilistic [6][7][8][9][10][11]). Formal verification of anonymity has been applied to a number of application domains, including electronic voting [12,13], electronic cash protocols [14], file sharing [15,16] and electronic healthcare [17].…”

Path Problems in Geographic Information Systems

“…Recently, Pan et al [126] added a k-anonymity privacy protection approach to further improve previous methods by protecting user privacy against identity theft. In [33], a more general approach for protecting user privacy is presented by studying the impact of query dependency on user privacy. Cryptography-based location protection methods might provide a better privacy protection, but they suffer from poor performance, and require specific infrastructure, which may not be supported by all LBS providers [67].…”