Investigation of patterns in cyber threats risk using data analytics and preference learning approaches
PhDs and postgraduate research
Funded PhD Project (international students only)
Operations and Systems Management
4 May 2021 (12pm GMT)
Candidates applying for this project may be eligible to compete for a Portsmouth Global PhD scholarship. Successful candidates will receive a scholarship to cover tuition fees at an international rate for three years, a stipend in line with the UKRI rate (£15,609 for 2021/22), and one return flight to London during the duration of the course.
The Faculty of Business and Law offers funding to support conference attendances and external training. You will also have the opportunity to apply for a placement support fund.
The work on this project could involve:
- Analysis of the relevant literature about cyber threats issues
- Identification of the existing cyber threat handling techniques
- Design of a comprehensive framework to address the shortcomings of the existing cyber threat handling techniques
- Validation and application of the framework in practice
In recent years, the threat and severity of cyber-attacks have increased. The world has and still is witnessing the most horrific cases of cyber-crimes linked to major data breaches, microchip bugs, crypto-jacking, fake news, disinformation, and many others since the last few years.
Every other day, we come across the news relating to cybersecurity threats such as ransomware, phishing, or IoT-based cybersecurity concerns. Nevertheless, the world is experiencing a whole new level of cybersecurity issues that businesses need to be aware of, not only do businesses need to be aware of, the decision-makers are also perplexed by recent cyber issues. In reality, a recent threat horizon study shows that under three primary threats (disruption, distortion, and deterioration) organizations will face cyber threats in the coming years.
For malicious hackers, these organizations make enticing targets, among the top are cloud security risks, data breach, misconfiguration, unstable interfaces and APIs, account hijacking, malicious insider threats, and Distributed Denial of Service (DDoS) attacks will continue to plague organizations that refuse to invest in a robust cloud security strategy. Different machine learning techniques and technologies have been used to help build securer, safer, and more resilient digital systems. Applying these techniques and technologies in practice is not straightforward.
Thus, this project aims to identify and predict the patterns in cyber threats risk using data analytics and preference learning approaches. Using data analytics and preference learning approaches, this project will help to identify and address the shortcomings in the existing methodologies and reduce cyber threats by jointly considering technical as well as user-related preferences of cyber threats risks. This project will also deliver tangible and intangible results with consequential impact and benefits to organisations and decision-makers.
You'll need a good first degree from an internationally recognised university (minimum upper second class or equivalent, depending on your chosen course) 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.
The successful candidate is expected to have good knowledge of one or combination of the following:
- Resilience, crisis and risk management
- Computer/Information system (IS), data analytics, machine learning
- Operational research
- Cyber security, IoT, Blockchain, AI (Artificial Intelligence)
How to apply
We’d encourage you to contact Dr Muhammad Shakir (email@example.com) 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.
Please also include a research proposal of 1,000 words outlining the main features of your proposed research design – including how it meets the stated objectives, the challenges this project may present, and how the work will build on or challenge existing research in the above field.
If you want to be considered for this funded PhD opportunity you must quote project code O&SM6231021 when applying.