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

Time-Based CAN Intrusion Detection Benchmark

Deborah Blevins (University of Kentucky), Pablo Moriano, Robert Bridges, Miki Verma, Michael Iannacone, and Samuel Hollifield (Oak Ridge National Laboratory)

Read More

ROV++: Improved Deployable Defense against BGP Hijacking

Reynaldo Morillo (University of Connecticut), Justin Furuness (University of Connecticut), Cameron Morris (University of Connecticut), James Breslin (University of Connecticut), Amir Herzberg (University of Connecticut), Bing Wang (University of Connecticut)

Read More

Understanding Worldwide Private Information Collection on Android

Yun Shen (NortonLifeLock Research Group), Pierre-Antoine Vervier (NortonLifeLock Research Group), Gianluca Stringhini (Boston University)

Read More

Differentially Private Health Tokens for Estimating COVID-19 Risk

David Butler, Chris Hicks, James Bell, Carsten Maple, and Jon Crowcroft (The Alan Turing Institute)

Read More