Towards trajectory anonymization: a generalization-based approach
SPRINGL '08: Proceedings of the SIGSPATIAL ACM GIS 2008 International Workshop on Security and Privacy in GIS and LBS, page 52-61. New York, NY, USA, ACM, (2008)Abstract
Trajectory datasets are becoming more and more popular due to the massive usage of GPS and other location-based devices and services. In this paper, we address privacy issues regarding the identification of individuals in static trajectory datasets. We provide privacy protection by definig trajectory k-anonymity, meaning every released information refers to at least k users/trajectories. We propose a novel generalization-based approach that applies to trajectories and sequences in general. We also suggest the use of a simple random reconstruction of the original dataset from the anonymization, to overcome possible drawbacks of generalization approaches.
Description
Towards trajectory anonymization: a generalization-based approach
