A Fast and Efficient Entity Resolution Approach for Preserving Privacy in Mobile Data

With the advent of mobile networking and the widespread adoption of smartphone devices, a number of location-based services have emerged, where users actively participate by sharing and receiving mobility data. However, the collection and analysis of user mobility data, such as user location information and trajectory data, especially when exploited together with external sources, such as social networks that often provide rich and publicly available information, can reveal sensitive user information. This paper proposes an approach based on entity resolution which enables users to disclose their mobility information without compromising their privacy, even if these data are linked with external publicly available information. We present detailed experimental results using four real datasets to illustrate that our approach is practical, efficient and effectively preserves privacy by eliminating potential links among the data.