Machine learning approach to identifying side channel attacks on cloud computer systems
PhDs and postgraduate research
Self-funded PhD students only
School of Computing
Applications accepted all year round
The work on this project could involve:
- Knowledge of Machine Learning
- Knowledge of Cyber Security
Side Channel attacks are the actions of stealing sensitive data by exploiting the vulnerability of a system. The initial work in this direction has successfully lead to the detection of side channel attacks based on Flush+Reload techniques against Advanced Encryption Standard (AES) algorithms. This project aims to develop a new universal framework to address all known side channel attacks mainly Flush+Reload, Prime+Probe, Flush+Flush and Evict+Reload techniques machine learning and statistical approaches.
Fees and funding
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).
2020/2021 fees (applicable for October 2020 and February 2021 start)
Home/EU/CI full-time students: £4,407 p/a*
Home/EU/CI part-time students: £2,204 p/a*
International full-time students: £16,400 p/a*
International part-time students: £8,200 p/a*
*All fees are subject to annual increase
You'll need a good first degree from an internationally recognised university 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.
Master or equivalent in Computer Science, Cyber Security or Artificial intelligence.
How to apply
We’d encourage you to contact Dr Mo Adda (firstname.lastname@example.org) to discuss your interest before you apply, quoting the project code.
When you are ready to apply, you can use our online application form. 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.
If you want to be considered for this PhD opportunity you must quote project code COMP4970220 when applying.