PrivLBS: Preserving Privacy in Location-Based Services

Abstract

Location-based services have been increasingly integrated into people’s daily activities. However, some of these services may not be trustworthy and lead to serious privacy breaches. While spatial transformation techniques such as location perturbation or generalization have been studied extensively, many of them only consider the locationat single timestamps without considering temporal correlations among the locations of a moving user, leaving the user’s location with no guarantees of privacy protection against attacks that would exploit this vulnerability. This work proposes a new technique for preserving data privacy, named PrivLBS, which ensures that the individual’s location will not be easily re-identified by malicious services. Extensive simulation experiments have been carried out to evaluate the efficiency of PrivLBS. Experimental results show that PrivLBS reaches higher protection compared to other related approaches over different kinds of attacks.