Contextualizing Security and Privacy of Software-Defined Vehicles: A Literature Review and Industry Perspectives

TL;DR

This paper reviews the security and privacy challenges of Software-Defined Vehicles through literature and industry insights, proposing a framework to enhance cybersecurity and privacy in modern automotive systems.

Contribution

It introduces a comprehensive security framework for SDV, integrating industry perspectives and addressing architectural, security, and privacy challenges.

Findings

Need for layered security mechanisms in SDV

Importance of harmonizing in-vehicle and cloud defenses

Addressing mixed-criticality architectural challenges

Abstract

The growing reliance on software in road vehicles has led to the emergence of Software-Defined Vehicles (SDV). This work analyzes SDV security and privacy through a systematic literature review complemented by an industry questionnaire across the automotive supply chain. The analysis is structured as four research questions and results in a security framework serving as a roadmap for SDV protection. The findings emphasize addressing mixed-criticality architectural challenges, deploying layered security mechanisms, and integrating privacy-preserving techniques. The results highlight the need to harmonize in-vehicle and cloud-based defenses to strengthen cybersecurity and V2X resilience in Intelligent Transportation Systems (ITS).