Protecting Children’s Digital Safety and Privacy in Smart Device Interactions
This project will develop a next-generation content filtering system specifically designed for children’s smart device interactions, integrating state-of-the-art federated learning, Large Language Models (LLMs), blockchain, and Explainable Artificial Intelligence (XAI) to enhance privacy, security, and interpretability.
Research Opportunities
Summary
The widespread adoption of smart devices among children has created significant challenges regarding digital safety and privacy. As frequent users of these devices, children are increasingly vulnerable to harmful online content, including age-inappropriate materials like pornography, violence, and other disturbing content. Current content filtering mechanisms, such as Net Nanny, while effective in blocking harmful websites and applications, predominantly rely on centralized systems. These systems often lack the ability to monitor children’s activities and interactions on legitimate applications, such as social media platforms like Facebook and streaming services like YouTube, raising serious concerns about their effectiveness in detecting harmful interactions. Furthermore, centralized approaches typically involve the collection and processing of children's data on central servers, which poses risks of potential data misuse or breaches. With increasing public and regulatory emphasis on safeguarding children’s digital privacy, there is an urgent need for a decentralized, privacy-preserving solution that effectively filters harmful content while ensuring that user data remains secure and private.
With the introduction of the Online Safety Act, public and regulatory emphasis on protecting children’s digital privacy is growing. The Act requires online service providers to implement protections against harmful content, enforce age verification, and conduct regular risk assessments. This legislation underscores the urgent need for a decentralized, privacy-preserving solution that effectively filters harmful content while keeping user data secure and private.
This PhD proposal aims to develop a next-generation content filtering system specifically designed for children’s smart device interactions, integrating state-of-the-art federated learning, Large Language Models (LLMs), blockchain, and Explainable Artificial Intelligence (XAI) to enhance privacy, security, and interpretability. By addressing both privacy and content safety, this research seeks to balance the need for robust content moderation with the preservation of user data privacy, offering a solution that is effective, ethical, and secure.
Objectives
- Develop Federated Learning Techniques: Create distributed content filtering methods across devices, minimizing the need for centralized data collection and mitigating privacy risks associated with centralized content analysis.
- Implement LLM-Based Models: Develop a model based on LLMs to understand and filter textual content effectively. This model will enable the system to accurately identify inappropriate content across various linguistic variations and contexts, thereby enhancing the relevance of content filtering.
- Utilize Blockchain for Model Weight Sharing: Establish a community-driven, blockchain-based federated learning model to facilitate the sharing of model weights among participating devices. This approach will ensure that updates are decentralized and tamper-proof, enhancing both the security and integrity of the model.
- Incorporate Explainable AI Techniques: Integrate XAI techniques to ensure the filtering model’s decision-making process remains interpretable. This transparency will allow parents, guardians, and stakeholders to understand why specific content is flagged, fostering trust in the system.
Potential Candidate Qualifications
- Strong academic background in cybersecurity, computer science, or a related discipline, with at least a 2:1 BSc or equivalent.
- Proficiency in programming languages such as Python and Java, with hands-on experience in developing machine learning algorithms.
- Demonstrated interest in research and a commitment to advancing the field of child safety in digital environments.
Supervisors
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Research Themes
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About our Research Degrees
We welcome specific ideas from applicants for a potential research degree topic. The University offers a number of potential self-funded topics in each School which you could consider developing your research project around.
It is not unusual for a proposed research degree topic to evolve as you progress through the application stage and even your future studies. This ensures the best match of your academic/professional experience with that of your supervisory team.
Occasionally, the University will also advertise available funded studentships, for very specific topics or subjects:
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Entry requirements
Entry Requirements for Research Degrees
Normal entry requirements are a first or upper second class honours degree from a University of the United Kingdom, or from an overseas University, or degree equivalent qualification, subject to the approval of Robert Gordon University.
Applicants holding other qualifications shall be considered on their merits and in relation to the nature and scope of the proposed research programme.
Applicants will normally register for an MSc/PhD or MRes/PhD with transfer to PhD dependent on satisfactory progress. However, applicants who already possess a Master’s degree which includes a significant research component could be registered directly for a PhD, subject to a satisfactory research proposal, and clear evidence of research expertise.
Some Research Degree Topics require employment experience, research experience and/or transcripts for international qualifications.
Contact researchdegrees@rgu.ac.uk to see if you are eligible.
English Language
Any applicant whose first language or language of previous University-level instruction is not English must normally demonstrate competence in English. This should be a score of IELTS 6.5 with 6.5 in all elements, or an approved equivalent.
We accept a variety of in-country and secure English language tests, find out more:
Please note, some courses may require a higher standard of English than stated in this page. Contact researchdegrees@rgu.ac.uk for further information.
Fees & Costs
For Academic Year 2024/2025
UK/EU Students
- Full time - £4,786 per academic year
- Part time MPhil/PhD - £2,870 per academic year
- Part time MRes/MSc by research - £2,390 per academic year
International Students
- Full time - £19,450 per academic year
- Part-time MPhil/PhD - £11,670 per academic year
- Part-time MRes/MSc by research - £9,720 per academic year
For Academic Year 2023/2024
UK/EU Students
- Full time - £4,712 per academic year
- Part time MPhil/PhD - £2,830 per academic year
- Part time MRes/MSc by research - £2,356 per academic year
International Students
- Full time - £18,700 per academic year
- Part-time MPhil/PhD - £11,220 per academic year
- Part-time MRes/MSc by research - £9,350 per academic year
Additional Costs
The following course-related costs are not included in the course fees:
- The cost of books that you may wish to purchase
- Accommodation and living costs
- Printing
Alumni Discount
Robert Gordon University is delighted to offer a 20% discount on course fees for all alumni who have graduated from RGU.
Scholarships and Financial Awards
Postgraduate research students will normally make their own arrangements for payment of fees. However you may qualify for a scholarship or financial award:
Funded Studentships
Occasionally, the University will also advertise available funded studentships, for very specific topics or subjects:
Disclaimer
For new intakes course fees are reviewed and published annually for each mode of delivery. Tuition fees are fixed for the duration of a course at the rate confirmed in the offer letter. For further information see:
How to Apply
Applications
All applications should be made via the University's online application for research students.
Before you apply, find out more about the application process, research proposal writing guides, routes and durations:
Our Research degrees usually start in February and October each year. There are no formal deadlines for you to submit your application, though we recommend you submit it as early as possible in order to ensure we can help you join us at your preferred time.
Completed application forms should be accompanied by:
- Degree certificate
- Statement of purpose, detailing why you would like to study this degree in the UK, and why you have chosen RGU.
- A short research proposal, in the range of 1,500 - 3,000 words, containing a rationale and background, study aims and objectives, a literature review, proposed research methods and a full reference list.
Further guidance on the application process:
English Language Requirements
All applicants whose first language is not from a recognised English speaking country will be asked to provide evidence of their English language skills as part of their offer to study at RGU.
Find out more about the English language qualification we accept:
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