Differential Privacy for Distributed Traffic Monitoring in Smart Cities

Marcus Gelderie, Maximilian Luff, Lukas Brodschelm

2024

Abstract

We study differential privacy in the context of gathering real-time congestion of entire routes in smart cities. Gathering this data is a distributed task that poses unique algorithmic and privacy challenges. We introduce a model of distributed traffic monitoring and define a notion of adjacency for this setting that allows us to employ differential privacy under continual observation. We then introduce and analyze three algorithms that ensure ε differential privacy in this context. First we introduce two algorithms that are built on top of existing algorithmic foundations, and show how they are suboptimal in terms of noise or complexity. We focus, in particular, on whether algorithms can be deployed in our distributed setting. Next, we introduce a novel hybrid scheme that aims to bridge between the first two approaches, retaining an improved computational complexity and a decent noise level. We simulate this algorithm and demonstrate its performance in terms of noise.

Paper Citation

in Harvard Style

Gelderie M., Luff M. and Brodschelm L. (2024). Differential Privacy for Distributed Traffic Monitoring in Smart Cities. In Proceedings of the 10th International Conference on Information Systems Security and Privacy - Volume 1: ICISSP; ISBN 978-989-758-683-5, SciTePress, pages 758-765. DOI: 10.5220/0012372700003648

in Bibtex Style

@conference{icissp24,
author={Marcus Gelderie and Maximilian Luff and Lukas Brodschelm},
title={Differential Privacy for Distributed Traffic Monitoring in Smart Cities},
booktitle={Proceedings of the 10th International Conference on Information Systems Security and Privacy - Volume 1: ICISSP},
year={2024},
pages={758-765},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012372700003648},
isbn={978-989-758-683-5},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 10th International Conference on Information Systems Security and Privacy - Volume 1: ICISSP
TI - Differential Privacy for Distributed Traffic Monitoring in Smart Cities
SN - 978-989-758-683-5
AU - Gelderie M.
AU - Luff M.
AU - Brodschelm L.
PY - 2024
SP - 758
EP - 765
DO - 10.5220/0012372700003648
PB - SciTePress