Adaptive and Resilient Secure Systems

Summary

Research Context

Positioned within Ulster University’s School of Computing, this research theme focuses on adaptive and resilient security for emerging AI-enabled and highly distributed digital systems.

The projects address two complementary challenges: securing software produced with Large Language Model (LLM) coding assistants and protecting dynamic Flying Ad Hoc Networks (FANETs).

Research will explore explainable and language-agnostic vulnerability detection, transfer learning and domain adaptation, alongside privacy-preserving federated learning for decentralised UAV networks.

Collectively, the theme aims to develop practical, trustworthy and scalable approaches that can detect, localise and explain security weaknesses while strengthening privacy, resilience and confidence in next-generation software and networked systems.

The projects directly address priority areas in Software/Cyber, strengthening Northern Ireland’s capability in cyber security, trustworthy AI, resilient digital infrastructure and privacy-preserving distributed systems, while supporting the Programme for Government priority to grow a globally competitive and sustainable economy.

We welcome applicants who are interested in projects in the following areas:

SAFE-GEN: Secure and Trustworthy AI-Generated Software through Explainable Vulnerability Detection

Supervisor Names: Dr Aftab Ali

Generative AI is transforming software development, but can we trust the security of AI-generated code? SAFE-GEN will investigate vulnerabilities introduced by Large Language Model (LLM) coding assistants and develop intelligent methods to detect, localise and explain them.

The PhD will explore language-agnostic vulnerability detection, transfer learning, domain adaptation and explainable AI across human-written and AI-generated code. A key goal is to identify vulnerabilities at method and line level, helping developers understand where and why security weaknesses occur.

Working with the BT Ireland Innovation Centre (BTIIC), the researcher will gain valuable industrial experience while developing practical approaches for secure AI-assisted software development.

Enhancing Security and Privacy in FANETs Using Federated Learning

Supervisor Names: Dr Hanif Ullah

Flying Ad Hoc Networks (FANETs) consist of cooperating Unmanned Aerial Vehicles (UAVs) used in applications such as environmental monitoring, disaster management, search and rescue, and surveillance.

Their high mobility, dynamic topology, and decentralised structure provide flexibility but create significant communication, security, and privacy challenges. Vulnerabilities include eavesdropping, spoofing, data interception, and malicious node attacks, while traditional centralised security mechanisms are often unsuitable.

Federated learning offers a promising decentralised solution by enabling UAVs to train machine learning models locally without sharing sensitive data. The proposed research aims to develop a secure, scalable federated learning framework tailored to FANET environments.

Applying to Multiple Projects: Applications for more than one PhD studentship are welcome, however if you apply for more than one PhD project within Computing, your first application on the system will be deemed your first-choice preference and further applications will be ordered based on the sequential time of submission.

If you are successfully shortlisted, you will be interviewed only on your first-choice application and ranked accordingly. Those ranked highest will be offered a PhD studentship.

In the situation where you are ranked highly and your first-choice project is already allocated to someone who was ranked higher than you, you may be offered your 2nd or 3rd choice project depending on the availability of this project.

The School of Computing at Ulster University holds Athena Swan Bronze Award since 2016 and is committed to promote and advance gender equality in Higher Education.  We particularly welcome female applicants, as they are under represented within the school.

Essential criteria

Applicants should hold, or expect to obtain, a First or Upper Second Class Honours Degree in a subject relevant to the proposed area of study.

We may also consider applications from those who hold equivalent qualifications, for example, a Lower Second Class Honours Degree plus a Master’s Degree with Distinction.

In exceptional circumstances, the University may consider a portfolio of evidence from applicants who have appropriate professional experience which is equivalent to the learning outcomes of an Honours degree in lieu of academic qualifications.

• Sound understanding of subject area as evidenced by a comprehensive research proposal detailing background, research questions, aims and methodology
• A comprehensive and articulate personal statement demonstrating interest in the subject area

Desirable Criteria

If the University receives a large number of applicants for the project, the following desirable criteria may be applied to shortlist applicants for interview.

• International applicants should hold, or expect to hold, a First Class Honours Degree in a relevant subject area
• International applicants should hold, or expect to hold a relevant Masters Degree at a level equivalent to a distinction at Ulster
• Work experience relevant to the proposed project
• Track record of peer reviewed publications

Equal Opportunities

The University is an equal opportunities employer and welcomes applicants from all sections of the community, particularly from those with disabilities.

Appointment will be made on merit.

Funding and eligibility

This project is funded by:

• Department for the Economy (DfE)
• Vice Chancellor's Research Scholarship (VCRS)

PhD Scholarships are available for this project and will cover:

• Tuition fees.
• A maintenance allowance of approximately £22,000 (exact rate is to be confirmed) per annum for three years, subject to satisfactory academic performance.
• A Research Training Support Grant (RTSG) of approximately £900 per annum.

To be eligible for these scholarships applicants must: be a UK or Irish national; or have pre-settled or settled status; or have indefinite leave to remain or enter.

Applicants should also meet the residency criteria which requires that they have lived in the EEA, Switzerland, the UK or Gibraltar for at least the three years preceding the start date of the research degree programme i.e. September 2027.

Applicants who already hold a doctoral degree or who have been registered on a programme of research leading to the award of a doctoral degree on a full-time basis for more than one year, or part-time equivalent, funded from any source, including self-financing students, are NOT eligible to apply for an award.

Students in full-time employment are not eligible for an award.

Due consideration should be given to financing your studies.

Part-time PhD scholarships may be available at a 0.5 pro rata rate of the full-time scholarship, which would require a six-year registration period.

The University will award a successful candidate one of the following scholarships for the project, depending on the funding available at the time an admissions offer is made:

1. Department for the Economy (DfE) PhD Scholarships
2. Vice Chancellor’s Research Scholarships (VCRS)

Please note that the Terms and Conditions for scholarships are subject to change for 2027/28.