# Roadmap for Cybersecurity in Autonomous Vehicles

arXiv: https://arxiv.org/abs/2201.10349 · HTML: https://mlsanity.com/paper/2201.10349/

## Key facts

- Cited by 5 papers in the map (data through 14 Oct 2026).
- Builds on 9 of its 42 references that are in the map.
- First posted on arXiv 19 Jan 2022.

## Builds on (most cited first, 9 of 9)

- [Knowledge-Enriched Distributional Model Inversion Attacks](https://mlsanity.com/paper/2010.04092/) (2020)
- [GIDS: GAN based Intrusion Detection System for In-Vehicle Network](https://mlsanity.com/paper/1907.07377/) (2019)
- [Securing Connected & Autonomous Vehicles: Challenges Posed by Adversarial Machine Learning and The Way Forward](https://mlsanity.com/paper/1905.12762/) (2019)
- [Object Removal Attacks on LiDAR-based 3D Object Detectors](https://mlsanity.com/paper/2102.03722/) (2021)
- [INDRA: Intrusion Detection using Recurrent Autoencoders in Automotive Embedded Systems](https://mlsanity.com/paper/2007.08795/) (2020)
- [LATTE: LSTM Self-Attention based Anomaly Detection in Embedded Automotive Platforms](https://mlsanity.com/paper/2107.05561/) (2021)
- [TENET: Temporal CNN with Attention for Anomaly Detection in Automotive Cyber-Physical Systems](https://mlsanity.com/paper/2109.04565/) (2021)
- [Resilient Cooperative Adaptive Cruise Control for Autonomous Vehicles Using Machine Learning](https://mlsanity.com/paper/2103.10533/) (2021)
- [Fortifying Vehicular Security Through Low Overhead Physically Unclonable Functions](https://mlsanity.com/paper/2106.02976/) (2021)

## Built on by (most cited first, 5 of 5)

- [Embodied AI: Emerging Risks and Opportunities for Policy Action](https://mlsanity.com/paper/2509.00117/) (2025)
- [Robust Perception Architecture Design for Automotive Cyber-Physical Systems](https://mlsanity.com/paper/2205.08067/) (2022)
- [R-TOSS: A Framework for Real-Time Object Detection using Semi-Structured Pruning](https://mlsanity.com/paper/2303.02191/) (2023)
- [Ethical Design of Computers: From Semiconductors to IoT and Artificial Intelligence](https://mlsanity.com/paper/2212.12508/) (2022)
- [UPAQ: A Framework for Real-Time and Energy-Efficient 3D Object Detection in Autonomous Vehicles](https://mlsanity.com/paper/2501.04213/) (2025)

## Abstract (arXiv)

Autonomous vehicles are on the horizon and will be transforming transportation safety and comfort. These vehicles will be connected to various external systems and utilize advanced embedded systems to perceive their environment and make intelligent decisions. However, this increased connectivity makes these vehicles vulnerable to various cyber-attacks that can have catastrophic effects. Attacks on automotive systems are already on the rise in today's vehicles and are expected to become more commonplace in future autonomous vehicles. Thus, there is a need to strengthen cybersecurity in future autonomous vehicles. In this article, we discuss major automotive cyber-attacks over the past decade and present state-of-the-art solutions that leverage artificial intelligence (AI). We propose a roadmap towards building secure autonomous vehicles and highlight key open challenges that need to be addressed.