# Advancing Security in Software-Defined Vehicles: A Comprehensive Survey and Taxonomy

arXiv: https://arxiv.org/abs/2510.09675 · HTML: https://mlsanity.com/paper/2510.09675/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 8 Oct 2025.

## Built on by (most cited first, 1 of 1)

- [Assessing the Operational Impact of Poisoning Attacks over Augmented 3D Point Cloud Public Datasets for Connected and Autonomous Vehicles](https://mlsanity.com/paper/2607.06484/) (2026)

## Abstract (arXiv)

Software-Defined Vehicles (SDVs) introduce innovative features that extend the vehicle's lifecycle through the integration of outsourced applications and continuous Over-The-Air (OTA) updates. This shift necessitates robust cybersecurity and system resilience. While research on Connected and Autonomous Vehicles (CAV) has been extensive, there is a lack of clarity in distinguishing SDVs from non-SDVs and a need to consolidate cybersecurity research. SDVs, with their extensive connectivity, have a broader attack surface. Besides, their software-centric nature introduces additional vulnerabilities. This paper provides a comprehensive examination of SDVs, detailing their ecosystem, enabling technologies, and the principal cyberattack entry points that arise from their architectural and operational characteristics. We also introduce a novel, layered taxonomy that maps concrete exploit techniques onto core SDV properties and attack paths, and use it to analyze representative studies and experimental approaches.