An automated consistency management approach for a privacy-aware electric vehicle architecture

Modern vehicles contain a number of highly connected embedded systems that generate, store, and process information and exchange it with their environment. Since a large part of this information is privacy-critical, privacy laws such as the GDPR of the European Union apply to it. In this work, we evaluate the privacy-criticality of exemplary data and data flows of the electric driving domain on a reference architecture. We categorize the ECUs of the architecture based on the criticality of the data they process and propose measures and technologies as building blocks that provide adequate privacy protection according to the requirements given by the GDPR.

To ensure that all requirements are met by the reference architecture, we propose a more principled solution that simplifies the mapping between an architecture and the measures. For this purpose, we propose an architecture description template in JSON and an algorithm for automated consistency checks that outputs the measures and the security extension needed per Electronic Control Unit (ECU) to comply with derived privacy requirements.