The Problem of Anonymisation on Graph Data

Applications are invited for a self-funded 3-year PhD.

The PhD will be based in the Faculty of Technology, and will be supervised by Dr Janka Chlebikova. This is a joint project with Dauphine University, Paris.

The problem of anonymisation of data has received significant attention over the past decade. To find good methods to protect data privacy becomes important task attracting lots of research interest.

Graph data can be used to represent networks, e.g. social networks like Facebook or LinkedIn, but also spreading of infectious diseases. The representation is based on graphs, where vertices correspond to the entities and edges reflect relationships between entities. Since graph data in the networks may be sensitive, sharing such type of data requires the use of various anonymisation techniques.

To achieve that, the idea is to preserve significant structural properties of the networks while ensuring anonymity of its entities. It means, a simple modification of the network’s properties is allowed to create several indistinguishable entities. Several anonymisation techniques have already been explored: generalisation group’s records following certain criteria in order to hide individual records, data perturbation, or k-anonymisation where each entity is considered anonymous if it is indistinguishable from at least (k-1) others.

Some of these models were also studied from an algorithmic point of view, as anonymisation by using clustering methods. Also the computation complexity of k-anonymisation have been studied including various heuristics to modify graphs using allowed vertex/edge operations.

The purpose of the PhD is to study anonymisation models represented on graph data transformed to the problems from graph theory, mainly from an algorithmic point of view. 

This is a joint project with Dauphine University, Paris. During the PhD there is an opportunity to undertake a research visit (2–4 months) in the partner institution.

Fees and funding

Visit the research subject area page for fees and funding information for this project.

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).

We’d encourage you to contact Dr Janka Chlebikova at janka.chlebikova@port.ac.uk to discuss your interest before you apply, quoting the project code.

If you want to be considered for this self-funded PhD opportunity you must quote project code COMP4500220 when applying.