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Artificial Intelligence, Security, IoT: Fully Funded PhD Studentship In Adversarial Learning in Edge Devices

Swansea University - Computer Science

Qualification Type: PhD
Location: Swansea
Funding for: UK Students, EU Students, International Students
Funding amount: £19,237 p.a.
Hours: Full Time
Placed On: 13th December 2024
Closes: 13th January 2025
Reference: RS728

Key Information

Funding provider(s): EPSRC DTP

Subject area(s): Artificial Intelligence, Security, IoT

Project start date: 1 October 2025

Supervisors: Dr. Lu Zhang, Prof. Xianghua Xie, Dr. Yang Liu

Aligned programme of study:  PhD in Computer Science

Mode of studyFull-time

Project description:

Edge devices, integral to the Internet of Things (IoT) and modern smart applications, have increasingly relied on artificial intelligence (AI) for efficient operation and decision-making. However, these AI-based systems are vulnerable to adversarial attacks, which can compromise their functionality and security. This project aims to investigate the vulnerability of machine learning models deployed on edge devices and develop robust adversarial learning techniques to defend against such attacks. The focus will be on identifying potential weaknesses in current edge computing frameworks and leveraging adversarial learning, edge computing and game theory to create novel methods to enhance their resilience. This includes developing algorithms capable of detecting and mitigating adversarial attacks, ensuring that edge devices can maintain secure and reliable operations even under hostile conditions. Our research will cover various applications of edge devices, including real-time data processing, autonomous decision-making, and network intrusion detection. By addressing these areas, we aim to create a framework that not only secures individual edge devices but also enhances the overall security of interconnected IoT systems. The outcomes of this project will provide critical insights and methodologies for deploying secure, AI-driven edge solutions, thereby fostering safer and more reliable IoT ecosystems.

Funding Details

Funding Comment

This scholarship covers the full cost of tuition fees and an annual stipend at UKRI rate (currently £19,237 for 2024/25).

Additional attending conferences expenses of up to £1,000 per year will also be available.

EPSRC DTP studentships are available to home and international students. Up to 30% of our cohort can comprise international students, once the limit has been reached, we are unable to make offers to international students.

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