Decision Support System on Cybersecurity Policies for Autonomous Vehicles

Funded PhD Studentship

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

  • 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
  • evaluate the effectiveness of cybersecurity policies at mitigating cyber threats posed to CAV, as well as their social impacts on drivers, manufacturers and stakeholders.


In this project, we would like to achieve

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

For potential impact, we aim to construct plausible evidence to aid the decision-making of policy-makers and wider adoption of CAV technology.

Supervisory Team:


Please contact Dr Tingting Li [Email] with your C.V. , transcripts and 2-page Research Proposal. A suggested structure for the proposal is below

  • The scope of your project (i.e. what are the research questions and problems?)
  • The current state of the art (i.e. summarise the existing literature that has been published on your chosen research topic)
  • Current limitations (i.e. identify the “gaps” in existing literature in relation to the scope of your project)
  • Proposed methods (i.e. what computational or modelling methods will you use to tackle the current limitations and develop new knowledge?)
  • Anticipated contribution to Computer Science (i.e. what will we know after your PhD that we do not know now?)


In response to the new [UKRI eligibility criteria], Cardiff University is pleased to announce that it will be offering International fee discounts for successful UKRI applicants. This approach ensures that students regardless of nationality or financial means will be able to apply for our UKRI studentships. Successful applicants will receive a fully-funded studentship and will not be charged the international fee difference. Up to 30% of our EPSRC DTP funded studentships are available to international applicants.

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.

Entry Requirements

A 2:1 Honours undergraduate degree or a master’s degree, in computing or a related subject. Applicants with appropriate professional experience are also considered.

Applicants for whom English is not their first language must demonstrate their proficiency by obtaining an IELTS score of at least 6.5 overall, with a minimum of 6.0 in each skills component. Please read our [English language requirements] for more details.


Deadline for full online application (may be extended if necessary): 28 May 2021

Apply now: [] 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.

Funding Notes

3.5 years Full Time or part-time equivalent. Tuition fees at the home/EU 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.