Location-based services (LBS) are gaining importance due to the advances in localization techniques and mobile communications. However, if they want to become a true success, they must guarantee the location privacy of their clients. To do so, trusted third parties are used, most of the time, to mediate between an LBS user and a provider, so that the former remains hidden from the latter.

Dunne et al. describe a location-blurring algorithm that aims to improve the privacy of its users, by reducing the accuracy of their locations. In this approach, simple squared areas represent users’ locations; the proposed algorithm reduces the accuracy of locations by increasing the size of the areas containing real locations. As a result, the uncertainty that an external observer has about the real location of a user is also increased.

The most interesting part of the paper, although not its main part, is its architecture. Instead of defining mobile users, LBS providers, and static targets, the authors consider mobile users as the targets of requesters (that is, other users). So, in this special architecture, a trusted middleware does not hide the real locations of requesters from LBS providers, but those of mobile targets from requesters.

Although the paper is well written and very easy to understand, the contribution is not very relevant because similar obfuscation algorithms have been proposed in the past. The lack of experimental results and the weakness of the attack model (for example, collusions are not considered) might raise some doubts about the resiliency of the proposal.

In conclusion, the paper points out an interesting research line, but there is still a long way to go to end up with a complete solution.