Advanced Persistent Threats (APTs) are considered and are often defined as the threats that are the most challenging to detect and defend against. Crucially, the advent of 5G not only accentuates existing advanced threats but also introduces new ones, for which existing security mechanisms are not always directly applicable.
This PhD project aims at improving 5G security against APTs by:
- designing and developing a decentralised threat detection method based on statistical and rule-based machine learning with the goal to assess the behaviour of the network and certain cells and their deviations from “standard” behaviour, in a manner that is dynamic and able to reconfigure automatically in time;
- designing and developing a game theoretic framework to support decision-making of the Defender (e.g. 5G infrastructure owner or 5G network operator) against a rational APT-style Attacker. The proposed framework will advance the current state of the art by enabling a precise analysis of the interactions between Defender and the Attacker (i.e. APT) providing “robust” decision support for the Defender.
The objectives of this PhD are:
- To identify APTs that are realistic in the context of 5G networks and define APT protection requirements
- To provide APT detection capabilities for 5G networks
- To provide dynamic response recommendations for ongoing APTs in 5G
This research is supported by the UK Government and it is in partnership with BT. The PhD student will work at the University of Surrey, at the SCCS (Surrey Centre for Cyber Security) and at the 5GIC (5G Innovation Centre).
If you are fascinated about security and privacy and you have knowledge of any of the following: machine learning, mobile networks, cyber security risk assessment or game theory, please contact the supervisor for any further enquiries about the post or apply directly!
The project will commence on the 1st October 2019, with a duration of 3.5 years.
- Bachelor degree in Computer Science (UK equivalent 1st classification)
- Interest in any of the following: cyber security, privacy, machine learning, game theory, mathematical optimisation cyber risk assessment
- Programming experience (any language)
- Analytical skills: knowledge of foundations of computer science; ability to think independently
- Strong verbal and written communication skills, both in plain English and scientific language for publication in relevant journals and presentation at conferences.
- Master’s degree (UK equivalent of Merit classification or above)
- Knowledge of cyber security and computer networks
- Experience in machine learning
- Experience in game theory or mathematical optimisation
- Experience of implementation and/or experimentation with verification tools
How to apply:
Applications can be made through our course page: https://www.surrey.ac.uk/postgraduate/computer-science-phd
Please state the project title and supervisor clearly on all applications.
For any queries, please enquire with Dr Manos Panaousis, at [email protected]