Hestia: Historically-enabled spatio-temporal information anonymity
Location-Based Services (LBSs) have long been established in several regions of the world to allow mobile users, equipped with positioning devices, access a set of spatially aware services. In this chapter, we introduce a privacy framework for LBSs that utilizes collected movement data to identify parts of the user trajectories, where user privacy is at an elevated risk. To protect the privacy of the user, the proposed methodology transforms the original requests into anonymous counterparts by offering trajectory K-anonymity. As a proof of concept, we build a working prototype that implements our solution approach and is mainly used for experimentation and evaluation purposes. Our implementation relies on a spatial DBMS that carries out part of the necessary analysis. Finally, through a set of experiments we demonstrate the effectiveness of the proposed approach to preserve the K-anonymity of the users for as long as the requested services are in progress. © 2010 by Nova Science Publishers, Inc. All Rights Reserved.