Exploring privacy-enhancing technologies in the automotive value chain

TL;DR

This paper investigates how privacy-enhancing technologies can be applied in the automotive industry by analyzing use cases, expert insights, and open-source tools to address privacy and security needs.

Contribution

It provides a detailed classification of automotive use cases and evaluates the applicability of PETs, offering insights into their implementation and limitations.

Findings

Identification of key automotive use cases for PETs

Classification of PETs suitability for different use cases

Discussion of challenges and limitations in applying PETs

Abstract

Privacy-enhancing technologies (PETs) are becoming increasingly crucial for addressing customer needs, security, privacy (e.g., enhancing anonymity and confidentiality), and regulatory requirements. However, applying PETs in organizations requires a precise understanding of use cases, technologies, and limitations. This paper investigates several industrial use cases, their characteristics, and the potential applicability of PETs to these. We conduct expert interviews to identify and classify uses cases, a gray literature review of relevant open-source PET tools, and discuss how the use case characteristics can be addressed using PETs' capabilities. While we focus mainly on automotive use cases, the results also apply to other use case domains.