Towards Privacy in Geographic Message Dissemination for Connected Vehicles

TL;DR

This paper proposes a privacy-preserving framework for geographic message dissemination in connected vehicles, ensuring relevant traffic information delivery while respecting user privacy without sacrificing efficiency.

Contribution

It introduces a novel privacy-by-design framework that maintains scalability and efficiency in geographic message dissemination for connected vehicles.

Findings

Framework achieves privacy preservation without efficiency loss

Scalable solution for real-time geographic message dissemination

Aligns with legal privacy regulations

Abstract

With geographic message dissemination, connected vehicles can be served with traffic information in their proximity, thereby positively impacting road safety, traffic management, or routing. Since such messages are typically relevant in a small geographic area, servers only distribute messages to affected vehicles for efficiency reasons. One main challenge is to maintain scalability of the server infrastructure when collecting location updates from vehicles and determining the relevant group of vehicles when messages are distributed to a geographic relevance area, while at the same time respecting the individual user's privacy in accordance with legal regulations. In this paper, we present a framework for geographic message dissemination following the privacy-by-design and privacy-by-default principles, without having to accept efficiency drawbacks compared to conventional server-client based approaches.