Resilience of connected autonomous vehicles under cyber attack

About the project

Connected autonomous vehicles must remain safe and reliable even under cyber attacks. This project will develop technologies that mitigate and recover from malicious attacks on these future vehicles. Combining cybersecurity, artificial intelligence, control engineering and real-world experimentation, you will help create resilient connected autonomous systems for future defence and civilian applications.

Connected autonomous vehicles are expected to play a major role in future transport, logistics and defence applications. However, their increasing dependence on sensors, wireless communications and artificial intelligence creates new vulnerabilities to cyber attacks. Malicious manipulation of vehicle sensors, communications or control algorithms could compromise safety and reliability.

This project will investigate how connected autonomous vehicles can be protected against cyber attacks while maintaining safe and resilient operation. The research will address fundamental questions including:

The project will adopt a cyber-physical systems approach, combining cybersecurity, artificial intelligence, systems and control engineering, autonomous vehicle technologies and digital twins. Potential methodologies include threat modelling, anomaly and intrusion detection, robust control and estimation methods, and fault tolerant decision making. The developed techniques will be validated experimentally using representative attack scenarios and our instrumented connected autonomous electric vehicle platform.

The research is highly relevant to future defence and security applications, where autonomous systems must operate reliably in contested and adverse environments. Outcomes are expected to include novel methods for attack detection, mitigation and recovery, enabling connected autonomous systems to maintain safety and performance despite cyber threats.

• how can cyber attacks on sensing, communication and control systems be detected and mitigated in real time?
• how do attacks propagate through complex autonomous vehicle architectures?
• how can autonomous systems continue to operate safely when subsystems are compromised or behaving maliciously?

Dr Erisa Karafili

• Formal methods techniques applied to security problems
• Attributing and investigating Cyber Attacks
• Threat Models for IoT devices and Hybrid systems

Supervisors

• Supervisors: Dr Anil Madhusudhanan Lecturer in Mobility Systems

Dr Anil Madhusudhanan

• Dr Anil Madhusudhanan: Lecturer in Mobility Systems

Entry requirements

You must have an undergraduate degree (at least UK 2:1 honours degree) or its international equivalent in one of the following:

Essential:

Experience in any combination of cybersecurity, autonomous systems, control, sensing, communications or data analysis may also be helpful, but applicants are not expected to have experience in all of these areas.

An interest in developing independent research, project planning and risk-management skills would be welcomed.

Relevant specialist skills can be developed during the PhD and through CDT training.

• cyber security
• computer science
• electronic engineering
• electrical engineering
• mechanical engineering
• mechatronics
• control engineering
• robotics
• mathematics
• physics
• a related discipline
• familiarity with, or experience in, programming using MATLAB, Python, C/C++ or similar tools

Fees and funding

For candidates looking to complete a PhD or EngD full-time we offer an enhanced tax-free stipend of up to £30,000 per year, along with a substantial budget for research, travel, and centre activities.

CISDnS is committed to promoting equality, diversity and inclusivity. We welcome all applicants regardless of their gender, ethnicity, disability, sexual orientation or age, and will give full consideration to applicants seeking flexible working patterns and those who have taken a career break or are transitioning into a new role. The University has a generous maternity policy, onsite childcare facilities, and offers a range of benefits to help ensure employees’ well-being and work-life balance.

We are pleased to announce that for 2027/28 entry, specific Centres for Doctoral Training (CDTs) at the University of Southampton have been selected to be part of a pilot programme of funding for UK doctoral candidates launched by the Department for Science, Innovation and Technology (DSIT) and UK Research and Innovation (UKRI). Now managed by the Department for Digital, Culture Media and Sport (DCMS), the funding is delivered through a strand of government’s new TechFirst skills programme. TechFirst will fund nationally, a stipend uplift for at least 500 domestic (UK only) doctoral students in priority technology areas over the next four years, strengthening the UK’s innovation pipeline and building a more inclusive, resilient and high-impact research ecosystem.

How to apply

Apply now

Please apply via the online portal and select:

Applications should include:

• Academic year: 2027/28
• If you will be full time or part time
• Faculty: Engineering and Physical Sciences
• Search for "complex integrated systems"
• Select either PhD or EngD – if you are unsure, select PhD
• Add the name of the supervisor in section 2 of the application.
• your CV (resumé)
• 2 academic references
• degree transcripts and certificates to date

Faculty of Engineering and Physical Sciences

For questions about applying, email our Doctoral College (doctoralcollege-admissions@soton.ac.uk) .

Project leader

For an initial conversation, email Dr Erisa Karafili (E.Karafili@soton.ac.uk) .

Research areas