Private Aggregation of Trajectories

Authors: Badih Ghazi (Google Research), Neel Kamal (Google), Ravi Kumar (Google Research), Pasin Manurangsi (Google Research), Annika Zhang (Google)

Volume: 2022
Issue: 4
Pages: 626–644
DOI: https://doi.org/10.56553/popets-2022-0125

Download PDF

Abstract: In this paper, we study the task of aggregating user-generated trajectories in a differentially private manner. We present a new algorithm for this problem and demonstrate its effectiveness and practicality through detailed experiments on real-world data. We also show that under simple and natural assumptions, our algorithm has provable utility guarantees.

Keywords: trajectories, aggregation, differential privacy

Copyright in PoPETs articles are held by their authors. This article is published under a Creative Commons Attribution-NonCommercial-NoDerivs license.