Privacy Protection of Automated and Self-Driving Vehicles (Dagstuhl Seminar 22042)

Abstract

This report documents the program and the outcomes of Dagstuhl Seminar 22042 “Privacy Protection of Automated and Self-Driving Vehicles”. The Seminar reviewed existing privacy-enhancing technologies, standards, tools, and frameworks for protecting personal information in the context of automated and self-driving vehicles (AVs). We specifically focused on where such existing techniques clash with requirements of an AV and its data processing and identified the major road blockers on the way to deployment of privacy protection in AVs from a legal, technical, business and ethical perspective. Therefore, the seminar took an interdisciplinary approach involving autonomous and connected driving, privacy protection, and legal data protection experts. This report summarizes the discussions and findings during the seminar, includes the abstracts of talks, and includes a report from the working groups. This talk opened the seminar with an overview over the field of automotive privacy and how it developed over the years. We started from early works on Car-to-Everything (C2X) and discussed how privacy was considered an important requirement from day one. From this perspective, C2X is an excellent example of privacy-by-design and privacy-by-default. We introduced how changing pseudonyms were designed as a mechanism to protect privacy and prevent location tracking, also highlighting its limitations and the need to balance and trade-off technical privacy against effort and efficiency of applications. As an example, we looked into tracking attacks that can easily reconstruct a vehicle’s path from anonymous position samples (if they are available with sufficiently high resolution).