Communication Efficiency for Federated Learning in Critical Infrastructure

Federated learning is a machine learning approach that enables multiple parties to collaborate in developing a shared model while safeguarding the distribution and privacy of their data. The application of federated learning to critical national infrastructure protection offers several advantages, including enhanced security, efficiency, and privacy. Nevertheless, various security issues and concerns persist. In this Ph.D. research, our focus is on addressing one of these challenges, specifically concentrating on Communication Efficiency within the context of federated learning for Critical National Infrastructure. We aim to discover novel techniques to minimize the volume of communication required between the central server and the participants. Our goal is to reduce the communication overhead while ensuring model security and accuracy.

Academic qualifications

A second class honour degree or equivalent qualification in automation & control, industry 4.0, cybersecurity.

English language requirement

IELTS score must be at least 6.5 (with not less than 6.0 in each of the four components). Other, equivalent qualifications will be accepted. Full details of the University’s policy are available online.

Application process

Prospective applicants are encouraged to contact the supervisor, Dr Naghmeh Moradpoor ([email protected]) to discuss the content of the project and the fit with their qualifications and skills before preparing an application. 

The application must include: 

Research project outline of 2 pages (list of references excluded). The outline may provide details about

• Background and motivation, explaining the importance of the project, should be supported also by relevant literature. You can also discuss the applications you expect for the project results.
• Research questions or
• Methodology: types of data to be used, approach to data collection, and data analysis methods.
• List of references

The outline must be created solely by the applicant. Supervisors can only offer general discussions about the project idea without providing any additional support.

• Statement no longer than 1 page describing your motivations and fit with the project.
• Recent and complete curriculum vitae. The curriculum must include a declaration regarding the English language qualifications of the candidate.
• Supporting documents will have to be submitted by successful candidates.
• Two academic references (but if you have been out of education for more than three years, you may submit one academic and one professional reference), on the form can be downloaded here.

Applications can be submitted here.

Download a copy of the project details here.