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Software-Defined FHE: Rethinking Homomorphic Encryption Libraries via Software-Defined Arithmetic Optimizations

School of Electronics, Electrical Engineering and Computer Science | PHD

Applications are now CLOSED
Funding
Funded
Reference Number
EEECS/2025/AS2
Application Deadline
28 February 2025
Start Date
1 October 2025

Overview

Number systems underpin computing broadly by encoding how numbers are represented and how key arithmetic operations are performed, thereby determining the efficiency and applicability of fundamental arithmetic operations. Recent advances in machine learning have highlighted the benefits of optimizing number systems for specific applications. This PhD project aims to deliver similar benefits for computations on encrypted data. Fully Homomorphic Encryption (FHE) enables data to remain encrypted while supporting arithmetic computations. This enables secure and privacy-preserved machine learning (ML) on encrypted data. However, ML on encrypted data is significantly slower than on unencrypted data, indicating the need for more efficient implementations and software libraries. Recent studies indicate that data redundancy and unoptimized arithmetic in FHE libraries prevent broader FHE adoption. An innovative approach, Software-Defined Computer Arithmetic, addresses these issues through software-defined number formats and tailored arithmetic operations, promising significant improvements in FHE performance.

The goal of this project is to explore software-defined computer arithmetic and develop new numerical formats with their corresponding customized arithmetic operations tailored for homomorphic encryption. A highly efficient software library will be created to facilitate the widespread use of FHE, making it suitable for processing encrypted data in machine learning environments.

Funding Information

To be eligible for consideration for a Home DfE or EPSRC Studentship (covering tuition fees and maintenance stipend of approx. £19,237 per annum), a candidate must satisfy all the eligibility criteria based on nationality, residency and academic qualifications.

To be classed as a Home student, candidates must meet the following criteria and the associated residency requirements:

• Be a UK National,
or • Have settled status,
or • Have pre-settled status,
or • Have indefinite leave to remain or enter the UK.

Candidates from ROI may also qualify for Home student funding.

Previous PhD study MAY make you ineligible to be considered for funding.

Please note that other terms and conditions also apply.

Please note that any available PhD studentships will be allocated on a competitive basis across a number of projects currently being advertised by the School.

A small number of international awards will be available for allocation across the School. An international award is not guaranteed to be available for this project, and competition across the School for these awards will be highly competitive.

Academic Requirements:

The minimum academic requirement for admission is normally an Upper Second Class Honours degree from a UK or ROI Higher Education provider in a relevant discipline, or an equivalent qualification acceptable to the University.

Project Summary
Supervisor

Dr Amir Sabbagh Molahosseini

a.sabbaghmolahosseini@qub.ac.uk

Research Profile


Mode of Study

Full-time: 3 or 3.5 years


Funding Body
Funding TBC
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