Abstract
In the rapidly developing Electric Vehicle (EV) charging infrastructure, ensuring user privacy during charging and billing processes has become a concern. Modern vehicles increasingly support Plug-and-Charge (PnC), a standard for direct authentication and billing of charging sessions without user interaction. However, within the PnC architecture, the exchange of sensitive data enables the e-Mobility service providers and charging station operators to build profiles of users' travel patterns and habits. In this paper, we present a novel approach that uses an Oblivious Random Access Machine (ORAM) as a privacy-preserving database to aggregate the consumption of the Electric Vehicles (EVs) at the charging station operator. In our scheme, the charging station operator cannot link individual charging sessions to specific vehicles, while the service provider only obtains the aggregated consumption over the complete billing period instead of details about individual charging sessions.
Link: www.usenix.org/system/files/vehiclesec25-lauser.pdf
Citation: Timm Lauser, Nergiz Yuca, Nikolay Matyunin, Stefan Katzenbeisser, Christoph Krauß. 2025. Oblivious Plug&Charge: A Privacy-Preserving EV Charging Scheme based on ORAM. In Proceedings of the 3rd USENIX Symposium on Vehicle Security and Privacy. USENIX Association. www.usenix.org/conference/vehiclesec25/presentation/lauser