An analysis of privacy preservation in electric vehicle charging

• Published in: Energy Informatics 2022-04, Vol.5 (1), p.1-27, Article 3
• Main Authors: Unterweger, Andreas, Knirsch, Fabian, Engel, Dominik, Musikhina, Daria, Alyousef, Ammar, de Meer, Hermann
• Format: Article
• Language: English
• Subjects: Analysis; Charging; Computer Science; Ecosystems; Electric vehicle; Electric vehicle charging; Electric vehicles; Information Systems and Communication Service; Infrastructure; Privacy; Review
• ISSN: 2520-8942; 2520-8942
• DOI: 10.1186/s42162-022-00190-y

Electric vehicles (EVs) are gaining widespread adoption, which requires expanding the charging infrastructure. This infrastructure is part of a complex ecosystem that consists of multiple entities interacting with each other and exchanging (often personal) user data. Such a heterogeneous system with multiple participants exchanging personal data poses severe privacy risks to users. State-of-the-art literature insufficiently covers privacy aspects of charging ecosystem use cases. In this paper, a profound analysis of this ecosystem with respect to privacy is provided: First, the EV charging ecosystem and its entities are defined. Second, high-level use cases for EV charging identified in literature are analyzed and used for defining data flows within the charging ecosystem. Third, the identified use cases are compared in terms of privacy guarantees and adherence to standards. Fourth, representative implementations of these use cases are evaluated, i.e., all actors and (unintended) data flows are described and potential privacy threats are identified and visualized. It is found that privacy is not sufficiently covered by standards and implementations of EV charging use cases from literature. Furthermore, recommendations and future directions for protecting user privacy in the EV charging ecosystem are derived. In summary, stricter adherence to standards and privacy by design are suggested.