About the Project
The convergence of 5G and 6G networks, the Internet of Things, edge computing, digital twins, and cyber physical systems is reshaping the global cybersecurity landscape at an unprecedented pace. As these technologies become embedded in critical infrastructure, healthcare, and smart cities, the security challenges they introduce are growing faster than existing frameworks can address. This PhD project offers a motivated candidate the opportunity to conduct original research at the intersection of…
artificial intelligence and network security, investigating cybersecurity challenges across this broad and rapidly evolving technological ecosystem, supported by an experienced supervisory team with an active publication record in cybersecurity and machine learning.
Project Highlights:
The work on this project will:
- Tackle real and rapidly evolving cybersecurity challenges across cutting edge technologies including 5G, 6G, IoT, digital twins, and cyber physical systems
- Freedom to identify and pursue an original research problem within a broad and dynamic domain, supported by an experienced supervisory team
- Develop expertise at the intersection of artificial intelligence and network security, two of the most in demand skills in the global technology workforce
- Contribute to research with direct relevance to UK national cybersecurity strategy and the security of critical national infrastructure
- Access to a collaborative research environment with links to partner universities and industry
- Suitable for candidates with a background in computer science, cybersecurity, electrical engineering, or telecommunications
Project description:
The convergence of 5G and 6G networks, the Internet of Things, edge computing, digital twins, and cyber physical systems is creating an interconnected technological ecosystem of unprecedented scale and complexity. This ecosystem underpins some of the most critical functions of modern society, spanning smart cities, autonomous transport, industrial automation, remote healthcare, and national infrastructure. As these technologies become deeply embedded in everyday life, the security challenges they introduce are growing in both sophistication and consequence.
The attack surface across this landscape is vast and continuously evolving. Connected devices, virtualised network functions, real time data pipelines, and digital replicas of physical systems all introduce vulnerabilities that traditional security approaches were never designed to address. Threats in this space are not static, and the research community has only begun to map the full scope of what adversaries can exploit as these technologies mature and converge.
This PhD project invites motivated candidates to investigate cybersecurity challenges within this broad and rapidly evolving domain. The student will identify a focused and original research problem of their own interest, whether that involves securing communication layers in next generation networks, addressing vulnerabilities in large scale IoT deployments, protecting digital twin systems from manipulation, or developing intelligent detection and response mechanisms for emerging threats in cyber physical environments. The research will combine network security analysis with machine learning methodology to produce both theoretical contributions and practical solutions.
This is an opportunity to work at the frontier of cybersecurity research, with scope to make a genuinely novel contribution to a domain that is shaping the future of global connectivity.
Applicants should hold a 2:1 honours degree or Masters in Computer Science, Cybersecurity, Electrical Engineering, or a related discipline. An interest in network security, applied machine learning, or emerging technologies is desirable.
General admissions criteria
You'll need a good first degree from an internationally recognised university (minimum upper second class or equivalent, depending on your chosen course) or a master’s degree in an appropriate subject. In exceptional cases, we may consider equivalent professional experience and/or qualifications.
English language proficiency at a minimum of IELTS band 6.5 with no component score below 6.0.
International students will require a study visa from UKVI to pursue the degree in the UK. If the research is in a sensitive or technological subject, the student may also need to secure an Academic Technology Approval Scheme (ATAS) certificate from the UK Foreign Office.
Specific candidate requirements
In addition to the standard admissions criteria above, candidates for this project should ideally demonstrate the following:
- A degree in Computer Science, Cybersecurity, Electrical Engineering, Telecommunications, or a closely related discipline
- Familiarity with networking concepts and communication protocols, including an awareness of how modern network infrastructures operate
- Some experience with machine learning or data science, whether through coursework, a dissertation, or independent study
- Programming proficiency, particularly in Python, which will be the primary language used in the research
- An awareness of current cybersecurity threats and emerging technology trends across domains such as IoT, 5G or next generation networks
- Strong analytical and problem solving skills with the ability to engage critically with research literature
The following are desirable but not essential:
- Prior research experience in network security, applied machine learning, or related areas
- Familiarity with simulation or network analysis tools
- A published or submitted paper in a relevant area
Candidates who can demonstrate genuine intellectual curiosity about the security challenges of emerging and converging technologies are strongly encouraged to apply, regardless of whether they meet every desirable criterion listed above.
How to Apply
We’d encourage you to contact Dr Nasreen Anjum (nasreen.anjum@port.ac.uk) to discuss your interest before you apply, quoting the project code.
When you are ready to apply, please follow the 'Apply now' link on the Computing PhD subject area page and select the link for the relevant intake. Make sure you submit a personal statement, proof of your degrees and grades, details of two referees, proof of your English language proficiency and an up-to-date CV. Our ‘How to Apply’ page offers further guidance on the PhD application process.
When applying please quote project code CMP10620529.
Funding Notes
Funding Availability: Self-funded PhD students only
PhD full-time and part-time courses are eligible for the UK Government Doctoral Loan (UK and EU students only - eligibility criteria apply).
Bench fees
Some PhD projects may include additional fees – known as bench fees – for equipment and other consumables, and these will be added to your standard tuition fee. Speak to the supervisory team during your interview about any additional fees you may have to pay. Please note, bench fees are not eligible for discounts and are non-refundable.