Privacy in Spatio-Temporal Databases: A Microaggregation-Based Approach

Abstract

Abstract. Technologies able to track moving objects such as GPS, GSM, and RFID, have been well-adopted worldwide since the end of the 20th century. As a result, companies and governments manage and control huge spatio-temporal databases, whose publication could lead to previously unknown knowledge such as human behaviour patterns or new road traffic trends (e.g., through Data Mining). Aimed at properly balancing data utility with users' privacy rights, several microaggregationbased methods for publishing movement data have been proposed. These methods are reviewed in this book chapter. We highlight challenges in the three stages of the microaggregation process namely, clustering, obfuscation, and privacy and utility evaluation. We also address some of these challenges by presenting yet another microaggregation-based method for privacy-preserving publication of spatio-temporal databases.

The Fréchet/Manhattan Distance and the Trajectory Anonymisation Problem

“…That justifies the use of heuristics in microaggregation-based approaches for trajectory anonymisation [24]. An additional challenge to be addressed is that distance measures between trajectories tend to be computationally expensive.…”