[Paper Review] Security of Connected and Automated Vehicles

Mashrur Chowdhury, Mhafuzul Islam+1 more|arXiv (Cornell University)|Dec 24, 2020

Vehicular Ad Hoc Networks (VANETs)Engineering48 references22 citations

TL;DR

This paper analyzes the cyberattack surface and security vulnerabilities in connected and automated vehicles (CAVs) within cyber-physical systems (CPS), proposing detection and mitigation strategies using emerging technologies such as AI, 5G, blockchain, and post-quantum cryptography. It identifies critical threats in CAV-CPS and evaluates advanced technologies as proactive defenses against current and future cyberattacks.

ABSTRACT

The transportation system is rapidly evolving with new connected and automated vehicle (CAV) technologies that integrate CAVs with other vehicles and roadside infrastructure in a cyberphysical system (CPS). Through connectivity, CAVs affect their environments and vice versa, increasing the size of the cyberattack surface and the risk of exploitation of security vulnerabilities by malicious actors. Thus, greater understanding of potential CAV-CPS cyberattacks and of ways to prevent them is a high priority. In this article we describe CAV-CPS cyberattack surfaces and security vulnerabilities, and outline potential cyberattack detection and mitigation strategies. We examine emerging technologies - artificial intelligence, software-defined networks, network function virtualization, edge computing, information-centric and virtual dispersive networking, fifth generation (5G) cellular networks, blockchain technology, and quantum and postquantum cryptography - as potential solutions aiding in securing CAVs and transportation infrastructure against existing and future cyberattacks.

Motivation & Objective

• To identify and analyze the expanding cyberattack surface in connected and automated vehicle (CAV) cyber-physical systems (CPS) due to increased connectivity.
• To examine existing and emerging security vulnerabilities in CAVs and their integration with roadside infrastructure and communication networks.
• To evaluate the potential of emerging technologies—such as AI, software-defined networking, edge computing, and blockchain—in enhancing CAV security.
• To propose detection and mitigation strategies for current and future cyber threats targeting CAV-CPS.
• To assess the role of post-quantum and quantum-resistant cryptography in securing long-term CAV infrastructure against future cryptographic attacks.

Proposed method

• Categorizes CAV-CPS attack surfaces based on vehicle-to-vehicle (V2V), vehicle-to-infrastructure (V2I), and vehicle-to-cloud (V2X) communication channels.
• Maps security vulnerabilities across communication protocols, data exchange mechanisms, and system architecture in CAVs.
• Evaluates the role of artificial intelligence in real-time anomaly detection and behavioral analysis for identifying potential cyber intrusions.
• Analyzes software-defined networking (SDN) and network function virtualization (NFV) for dynamic, programmable network security policies in CAV environments.
• Investigates edge computing for low-latency, localized threat detection and response at the network periphery.
• Examines information-centric networking (ICN), virtual dispersive networking, and 5G for improved data integrity, scalability, and secure communication in CAVs.
• Assesses blockchain for securing data provenance, access control, and secure logging in distributed CAV systems.
• Reviews post-quantum and quantum-resistant cryptographic algorithms as long-term defenses against future quantum computing threats.

Experimental results

Research questions

• RQ1 What are the primary attack surfaces and security vulnerabilities in connected and automated vehicle cyber-physical systems (CAV-CPS)?
• RQ2 How can emerging technologies such as AI, 5G, and blockchain be leveraged to detect and mitigate cyberattacks in real time within CAV environments?
• RQ3 What role do edge computing and software-defined networking play in enhancing the resilience and responsiveness of CAV security architectures?
• RQ4 How can post-quantum and quantum-resistant cryptography protect CAV systems against future threats from quantum computing?
• RQ5 What are the architectural and protocol-level security challenges in integrating CAVs with roadside infrastructure and cellular networks?

Key findings

• The integration of CAVs into cyber-physical systems significantly expands the attack surface due to extensive V2X communication and system interdependencies.
• AI-driven anomaly detection can improve real-time identification of malicious behaviors in CAV networks with low false-positive rates.
• 5G and edge computing enable low-latency, localized threat response, reducing reliance on centralized systems and improving resilience.
• Blockchain technology enhances data integrity and auditability in CAV systems by enabling tamper-proof logging and access control.
• Post-quantum cryptographic algorithms such as lattice-based and hash-based schemes show strong potential for securing CAV communications against future quantum attacks.
• The convergence of SDN, NFV, and ICN enables more flexible and secure network management, reducing attack vectors in CAV communication infrastructures.