Andreas Unterweger, Fabian Knirsch, Clemens Brunner and Dominik Engel (Center for Secure Energy Informatics, Salzburg University of Applied Sciences, Puch bei Hallein, Austria)

The increasing amount of electric vehicles and a growing electric vehicle ecosystem is becoming a highly heterogeneous environment with a large number of participants that interact and communicate. Finding a charging station, performing vehicle-to-vehicle charging or processing payments poses privacy threats to customers as their location and habits can be traced. In this paper, we present a privacy-preserving solution for grid-to-vehicle charging, vehicle-to-grid charging and vehicle to-vehicle charging, that allows for finding the right charging option in a competitive market environment and that allows for built-in payments with adjustable and limited risk for both, producers and consumers of electricity. The proposed approach builds on blockchain technology and extends a state-of-the-art protocol with payments, while still preserving the privacy of the users. The protocol is evaluated with respect to privacy, risk and scalability. It is shown that pseudonymity and location privacy (against third parties) is guaranteed throughout the protocol, even beyond a single protocol session. In addition, both, risk and scalability can be adjusted based on the used blockchain.

View More Papers

WIP: Interrupt Attack on TEE-protected Robotic Vehicles

Mulong Luo (Cornell University) and G. Edward Suh (Cornell University)

Read More

Hey Alexa, is this Skill Safe?: Taking a Closer...

Christopher Lentzsch (Ruhr-Universität Bochum), Sheel Jayesh Shah (North Carolina State University), Benjamin Andow (Google), Martin Degeling (Ruhr-Universität Bochum), Anupam Das (North Carolina State University), William Enck (North Carolina State University)

Read More

QPEP: An Actionable Approach to Secure and Performant Broadband...

James Pavur (Oxford University), Martin Strohmeier (armasuisse), Vincent Lenders (armasuisse), Ivan Martinovic (Oxford University)

Read More

WIP: On Robustness of Lane Detection Models to Physical-World...

Takami Sato (UC Irvine) and Qi Alfred Chen (UC Irvine)

Read More