Postgraduate Research Scholarship: Developing Sustainable Intrusion Detection Systems for Industrial IoT by Leveraging Digital Twin and Signal Processing

The rapid adoption of Industrial Internet of Things (IIoT) technologies has transformed manufacturing, offering greater efficiency, real-time monitoring, and data-driven decision-making. However, this interconnectivity introduces significant cybersecurity vulnerabilities, leaving systems exposed to cyber-attacks. Traditional intrusion detection systems (IDS) often fall short in handling the real-time, large-scale data demands of IIoT and lack sustainability considerations, such as energy efficiency. This research proposes a sustainable, high-performance IDS that leverages digital twin technology and advanced signal processing to detect cyber threats in real-time while minimising energy consumption. Digital twins, as virtual replicas of physical systems, enable continuous monitoring and anomaly detection with minimal latency. Combined with efficient signal processing, this approach enhances detection accuracy while optimizing resource use, supporting cybersecurity and sustainability in IIoT networks. This study aims to develop a low-energy IDS solution tailored to IIoT’s unique security needs, balancing robust threat detection with reduced energy demands. By integrating digital twins and resource-efficient signal processing, this research sets a new standard for sustainable cybersecurity in IIoT.

The PhD candidate undertaking this research will gain expertise in cybersecurity, IIoT, signal processing, and artificial intelligence. The project offers access to state-of-the-art research facilities at the University of Greenwich, where cutting-edge cybersecurity solutions for industrial systems are developed. Throughout the project, the candidate will be encouraged to publish findings in high-impact journals, present at international conferences, and contribute to the growing body of knowledge on IIoT security.

This PhD project presents an exciting opportunity for researchers passionate about cybersecurity, artificial intelligence, and industrial automation to contribute to a high-impact area of research. The growing interconnectivity of industrial systems highlights the urgency of developing robust and efficient security mechanisms, making this research both relevant and essential for future IIoT deployments. The successful development of a Digital Twin-enabled IDS will not only improve the cybersecurity of industrial networks but also establish a foundation for further advancements in intelligent, self-learning security systems. Through industry collaborations and research contributions, this project will pave the way for future innovations in IIoT security and sustainable cyber defence strategies.

The PhD candidate will work under the primary supervision of Dr Kamran Pedram at the Centre for Sustainable Cyber Security (CS2) (https://www.gre.ac.uk/research/groups/sustainable-cyber-security-cs2).

The University of Greenwich (through CS2) has been recently recognised by the UK government as a NCSC Academic Centre of Excellence in Cyber Security Research

(https://www.ncsc.gov.uk/information/academic-centres-excellence-cyber-security-research).

Funding

Successful candidate will receive a contribution to tuition fees equivalent to the university’s Home rate, currently £5,006 (FT) or pro-rata (PT), for the duration of their scholarship. International applicants will need to pay the remainder tuition fee for the duration of their scholarship. The fee is subject to annual increase.

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