Trustworthy Intelligent Network Systems

As intelligent systems become more ubiquitous, Cyber Security is becoming more and more important with the increasing integration of communication interfaces in various network systems, such as vehicular ad-hoc networks, mobile ad-hoc networks, controller areas networks and in-vehicle infotainment systems.

One of the key challenges is to make these systems safe, secure, reliable, and hence less vulnerable to cyber threads. Recently, there is a growing interest in using AI and machine learning and formal verification in developing safe and secure networks. Machine learning offers automatically identifying security incidents and cyber threats and malicious attacks as well as automatically responding to them at run-time. Formal verification and model-based testing on the other hand play an important role in designing safe and secure systems by verifying system correctness and requirements at design-time. These methods can provide the intelligent capability to enhance functional safety and security and eliminates system vulnerabilities, which allows providing guidance for gapless system design, and for checking that an artefact has no points of entry for the adversary.

This project is aiming to analyse cyber security vulnerabilities of communication network systems using cutting-edge machine and deep learning methods as well as verification and testing techniques; and to develop safe, secure and reliable systems by defining mitigation strategies to defend against potential cyber threats. The project also aims to verify the cyber security standard compliance for these network systems. The project has many application areas, including smart cars, smart cities and IoT systems, where secure connection and control are key for operational safety.

Eligibility:

Candidates are expected to hold (or be about to obtain) a minimum 2:1 honours degree (or equivalent) in a related area / subject, e.g. Computer Science, Mathematics, Formal Methods, Cyber Security, Computer Networks, etc. MSc, MA or relevant experience in a related discipline is highly desirable.

How to apply

Formal applications can be submitted via the University of Bradford web site; applicants will need to register an account and select 'Full-time PhD in Computer Science' as the course, and then specify the project title in the 'Research Proposal' section.

About the University of Bradford

Bradford is a research-active University supporting the highest-quality research. We excel in applying our research to benefit our stakeholders by working with employers and organisations world-wide across the private, public, voluntary and community sectors and actively encourage and support our postgraduate researchers to engage in research and business development activities.

Positive Action Statement

At the University of Bradford our vision is a world of inclusion and equality of opportunity, where people want to, and can, make a difference. We place equality and diversity, inclusion, and a commitment to social mobility at the centre of our mission and ethos. In working to make a difference we are committed to addressing systemic inequality and disadvantages experienced by Black, Asian and Minority Ethnic staff and students.

Under sections 158-159 of the Equality Act 2010, positive action can be taken where protected group members are under-represented. At Bradford, our data show that people from Black, Asian, and Minority Ethnic groups who are UK nationals are significantly under-represented at the postgraduate researcher level. 

These are lawful measures designed to address systemic and structural issues which result in the under-representation of Black, Asian, and Minority Ethnic students in PGR studies.