1024ºË¹¤³§

Applications are invited for a self-funded, 3 year full-time or 6 year part-time PhD project.

The PhD will be based in the School of Computing and will be supervised by Dr Mo Adda, Dr Alex Gegov and Dr Rinat Khusainov.

The fast development and improvement of IoT devices open more doors to new challenges in digital forensics fuelled by cyber enabled and dependent crime activities. The mobility of these IoT devices and their potential involvements in international crimes further put the investigators in difficult positions when accessing and retrieving evidence from the IoT environments, which include devices, networks and the cloud gyrating the resource limitations, volatility and data sharing. Moreover, creating reports that might emerge from international investigations across different legislations might be a significant obstacle in a court of law. 

This project will be based on an existing work where the routing mechanisms and the DNA identifications of IoT devices have been developed.  The aim of this new project is to propose a generic framework based on fuzzy and machine learning algorithms to operate on hierarchical servers in international context ranging from investigations, imaging, analysis, reporting until standing in a court of law, as an expert witness, for instance. Fuzzy logic approaches will be considered to assess the accuracy of the report in an international context, and the machines algorithms examine the possibilities of identifying, classifying and weighting crime related evidence. In addition, the formal methods will be adopted to verify and articulate the implicit assumptions of the framework. 

In the previous work, we proposed a Hybrid Forensic IoT Server model, which registers devices and stores their data for examination purposes. We have published a book chapter and several papers, as outcome.  The initial database to maintain the identities and information about the IoT devices is tested at the 1024ºË¹¤³§ Forensic Lab.  The lab provides several resources and a good working environment to develop the framework for this new PhD project.

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  (UK and EU students only).

Bench fees

Some PhD projects may include additional fees – known as bench fees – for equipment and other consumables, and these will be added to your standard tuition fee. Speak to the supervisory team during your interview about any additional fees you may have to pay. Please note, bench fees are not eligible for discounts and are non-refundable.