Protection for Connected and Autonomous Vehicles against Cooperative Deception Attacks

The number of passenger vehicles on UK roads has reached 40m in 2022, resulting in increased travel times and congestion at the inconvenience of 115hrs per citizen per year.

Intelligent traffic management is required to optimise the control and routing of vehicles to battle congestion and its side effects, and Connected Autonomous Vehicles (CAVs), which can extend the capabilities of traffic management systems and improve efficiency and safety for passengers, are entering the market.

These new technologies are being released without adequate testing and consideration of how they could be vulnerable to misuse.

The challenges associated with maintaining a strong security posture in intelligent transport management approaches are significant. Trust can be compromised when an individual is engaging in deceitful behaviour.

Detection is required but has significant challenges: (i) decentralised architecture makes it challenging to have oversight and detect deceitful behaviour, (ii) different vehicle manufacturers and models result in heterogeneity making it difficult to detect unusual and deceitful behaviour.

The aim of this project is to discover new knowledge to understand and mitigate cooperative multi-agent deceptive CAVs in smart traffic infrastructure through the cross-discipline understanding of the technologies, how they are perceived, and how they can be misused.