Funding

Self-funded PhD students only

Project code

COMP5461021

Department 

School of Computing

Start dates

October and February

Closing date

Applications accepted all year round

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 work on this project could involve:

  • Machine learning and fuzzy logic
  • Network routing for IoT devices
  • Formal methods
  • Digital Forensics and investigations of IoT devices

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 University of Portsmouth Forensic Lab.  The lab provides several resources and a good working environment to develop the framework for this new PhD project.

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).

2021/2022 fees (applicable for October 2021 and February 2022 start)

PhD and MPhil

Home/EU/CI full-time students: £4,500 p/a**

Home/EU/CI part-time students: £2,250 p/a**

International full-time students: £17,600 p/a*

International part-time students: £8,800 p/a*

PhD by Publication 

External candidates: £4,407*

Members of staff: £1,720 

All fees are subject to annual increase. If you are an EU student starting a programme in 2021/22 please visit this page.

*This is the 2020/21 UK Research and Innovation (UKRI) maximum studentship fee; this fee will increase to the 2021/22 UKRI maximum studentship fee when UKRI announces this rate in Spring 2021.

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.

Entry requirements

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.

Cyber security and digital Forensics, minimum knowledge of machine learning and artificial intelligence, big data and database.

How to apply

We’d encourage you to contact Dr Mo Adda (mo.adda@port.ac.uk) to discuss your interest before you apply, quoting the project code.

When you are ready to apply, please follow the 'Apply now' link on the Computing PhD subject area page and select the link for the relevant intake. 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. 

When applying please quote project code: COMP5461021

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