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

Authors Frank Kargl, Ioannis Krontiris, André Weimerskirch, Ian Williams, Nataša Trkulja and all authors of the abstracts in this report

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Author Details

Frank Kargl
  • Universität Ulm - Ulm, DE
Ioannis Krontiris
  • Huawei Technologies - München, DE
André Weimerskirch
  • Lear Corporation and University of Michigan Transportation Research Institute - Ann Arbor, US
Ian Williams
  • University of Michigan - Ann Arbor, US
Nataša Trkulja
  • Universität Ulm - Ulm, DE
and all authors of the abstracts in this report

Cite AsGet BibTex

Frank Kargl, Ioannis Krontiris, André Weimerskirch, Ian Williams, and Nataša Trkulja. Privacy Protection of Automated and Self-Driving Vehicles (Dagstuhl Seminar 22042). In Dagstuhl Reports, Volume 12, Issue 1, pp. 83-100, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2022)
https://doi.org/10.4230/DagRep.12.1.83

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.

Subject Classification

ACM Subject Classification
  • Security and privacy → Human and societal aspects of security and privacy
  • Security and privacy → Privacy protections
  • Security and privacy → Privacy-preserving protocols
Keywords
  • automotive security and privacy
  • privacy and data protection

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