or
Looking to list your PhD opportunities? Log in here.
Research Group
Cyber Security and Networking Research Group
Computing, Informatics and Applications Research Group
Proposed supervisory team
Theme
Cyber Security, Artificial Intelligence, Machine Learning, Data Science and Applications
Summary of the research project
Mankind has witnessed several crises in recent years, including natural environmental disasters and the pandemic. Digital communication plays a crucial role during a crisis, particularly when people want to share time-critical, current, and relevant information in real-time. In fact, depending on the nature of the crisis, if physical communication is restricted or limited, digital media becomes the primary information source, e.g., the COVID-19 pandemic. Digital and social media resources face several challenges during a crisis, and one of the main challenges is around misinformation: like trusting the content, authors, data, etc. Privacy of users and compliance with data protection regulations have proven to be a particularly critical challenge.
The proposed research aims to address the privacy challenges of using social and digital media during a crisis, both environmental disasters (e.g., caused by climate change) and pandemics (e.g., COVID-19). The main goal of this study is to identify the reasons for privacy issues (i.e., personal data breach) which can cause successful cyber scams and breaches of national/international data regulations (e.g., GDPR, UK data protection act, etc.) during a crisis.
The study results will help us implement solutions to tackle the digital media cyber security and privacy challenges in future climate or health crises. This study will also identify the psychological root causes of sharing personal data with unauthorised persons, which might cause a successful cybercrime and/or breach of data protection regulation during a crisis. The list of causes can be used as a reference in future experimental studies. Different digital media content (such as news, etc.) will be simulated in a lab environment. The data collected from these studies will be used to build a machine-learning model to predict digital media user behaviour and concerns during a crisis. Such a system can protect the public interests and, at the same time, support governmental and non-profit.
Where you'll study
Funding
This project is self-funded. Details of studentships for which funding is available are selected by a competitive process and are advertised on our jobs website as they become available.
Next steps
If you wish to be considered for this project, you will need to apply for our Computer and Information Science PhD. In the section of the application form entitled 'Outline research proposal', please quote the above title and include a research proposal.
The university will respond to you directly. You will have a FindAPhD account to view your sent enquiries and receive email alerts with new PhD opportunities and guidance to help you choose the right programme.
Log in to save time sending your enquiry and view previously sent enquiries
The information you submit to Anglia Ruskin University ARU will only be used by them or their data partners to deal with your enquiry, according to their privacy notice. For more information on how we use and store your data, please read our privacy statement.
Based on your current searches we recommend the following search filters.
Check out our other PhDs in Cambridge, United Kingdom
Start a New search with our database of over 4,000 PhDs
Based on your current search criteria we thought you might be interested in these.
Security and Privacy Enhancing Technologies for Trustworthy Large Language Models
University of Reading
Model-based health economic evaluation of interventions for improving primary healthcare for patients with non-communicable diseases (NCDs) during severe flooding in India
University of Birmingham
Cyber Security, Artificial Intelligence, Machine Learning and Blockchain Technology: Mitigating Cyber Attacks and Detecting Malicious Activities in Network Traffic
University of Bradford