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EPSRC DTP studentship in Cyber Security Analytics: Decision Support System on Cybersecurity Policies for Autonomous Vehicles

   Cardiff School of Computer Science & Informatics

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  Dr Tingting Li, Prof M Williams  No more applications being accepted  Competition Funded PhD Project (UK Students Only)

About the Project

EPSRC DTP studentship in Cyber Security Analytics: Decision Support System on Cybersecurity Policies for Autonomous Vehicles

Project Summary

Connected Autonomous Vehicles (CAV) are already being developed and deployed across various sectors at a rapid pace. It brings potential to enhance road safety and save lives, however, due to the autonomous nature and often being highly interconnected, CAV have safety threats of their own. These threats could range from cyber-attacks leveraging the increasing levels of connectivity of CAV, to unexpected results when operating in an uncontrolled environment. The wide use of AI technology in CAV further heightens the risk of cyber-attacks. Ongoing research is investigating the limitations and vulnerabilities of AI and how these technologies could increase the opportunities for the adversary to implement attacks against CAV. Currently, many developments of CAV technologies overlook the trustworthiness, responsibility and security of CAV, which could lead to low public acceptability of CAV and thus compromise widespread adoption of autonomous vehicles in society.

To be able to safely adopt and trust AI and other technologies used in CAV, they need to be developed and tested within a social and legal context. Proactive measures should be implemented such as guidance, standards and policies, to regulate the design and deployment of CAV. Addressing these new cyber threats posed to CAV is now a top priority for policy-makers, regulators, and industry officials. The NHTSA cybersecurity guidelines provide a good initial framework for this purpose. Nevertheless, it is in general difficult for the public, policy-makers and manufacturers to make judgement and decisions about the cybersecurity of CAV. This PhD studentship aims to i) generate evidence derived from both “technology and society” to help the public to understand the opportunities and cyber threats of CAV, and decide the optimal cybersecurity policies for CAV, and ii) evaluate the effectiveness of cybersecurity policies at mitigating cyber threats posed to CAV, as well as their social impacts on drivers, manufacturers and stakeholders.


i) Formalising attack scenarios against CAV with the focus on AI models adopted in planning and perception through Vehicle-to-Vehicle (V2V) and Vehicle-to-Infrastructure (V2X). This task is expected to collaborate with another DTP PhD studentship which is looking at trustworthy AI for cybersecurity

ii) Through simulation and testbeds provided by industry collaborators, evaluate the effectiveness of candidate cybersecurity policies on mitigating cyber threats posed to CAV

iii) Studying the public acceptability of cybersecurity policies for CAV, including the impact on drivers’ behaviours and attitudes, political views and public awareness. A social simulation needs to be designed to provide a more informed evaluation of cybersecurity policies and identify the best policy enforcement strategies

iv) develop an integrated tool for decision support and optimisation for policy-making, taking into account cybersecurity defence, regional laws, constraints, social and economic impacts. In this way, the optimal cybersecurity policies can be decided through a multi-disciplinary effort of social, legal and technical assessment.

Potential impact

We aim to construct plausible evidence to aid the decision-making of policy-makers and wider adoption of CAV technology.

Application format

Please provide the following information in your application

  • Academic background – we are seeking creative and energetic individuals from a range of backgrounds. We require a 1st or 2:1 at first degree level and/or or distinction at Masters degree level to apply. ​Example degree subjects include (but are not limited to): computer science, psychology, criminology, sociology, law, and business. We also welcome those who have significant relevant work experience.​
  • Describe any experience of research​
  • Write a short statement on what you understand the topic of cyber security analytics to be and what excites you about it​
  • Write a short statement on how your experience fits to the project to which you have applied, and how you would approach the project
  • Write a short statement on why you would like to undertake PhD research in a multi-disciplinary cohort, and how you think the experience will benefit your career in comparison with studying as an individual student. 

Deadline for applications – 30th July 2021

Apply online:

Applicants should select Doctor of Philosophy, with a start date of Oct 2021. In the research proposal section of your application, please specify the project title and supervisors of this project. In the funding section, please specify that you are applying for advertised funding from EPRSC DTP.


3.5 years Full Time or part-time equivalent. Tuition fees at the home rate (£4,500 in 2021/22) and an annual stipend equivalent to current Research Council rates (£15,609 stipend for academic year 2021/22), plus support for travel/conferences/consumables.

Shortlisting and assessment process

We will hold online interviews (date TBC)

We will ask for a 15 minute presentation with maximum 4 slides

  • Why I want to do a PhD​
  • Why I want to join this cohort​
  • What will we know when I’m finished that we don’t know now?​
  • What will the impacts of my research be?​

All students face a single panel comprised of 4 supervisors advertising studentships, the Hub Director as chair, and the Hub EDI lead​

For more information, please contact the hub’s Academic Lead: Professor Pete Burnap, [Email Address Removed]

Funding Notes

The PhD studentship is fully funded via the EPSRC DTP Hub in Cyber Security Analytics for 3.5 years to start Oct 2021.
Unfortunately, due to funding constraints, international fees cannot be covered in this instance.

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