A postgraduate student team from the Department of Electrical and Electronic Engineering (EEE), Faculty of Engineering, The University of Hong Kong (HKU), has been awarded the 1st Runner Up Award of the Institution of Engineering and Technology (IET) Young Professionals Exhibition & Competition (YPEC) 2025.
YPEC is an annual showcase and competition that brings together young engineers and students from diverse disciplines to present their innovations in engineering and technology. Organised by the IET and co-organised by EMSD (機電工程署), the event serves as a platform for emerging talent to demonstrate their research and development achievements.
The HKU team—comprising Dr. Zhenglong LI, Mr. Songshi DOU, and Mr. Tianqin YANG—was supervised by Dr. Vincent W.L. TAM (Principal Lecturer of HKU EEE) and Prof. Lawrence K. YEUNG (Associate Dean (RPg) of Faculty of Engineering). Their award-winning project, titled “Developing A Coarse-to-Fine Grained Knowledge Refinement Framework for Network Intrusion Detection System”, impressed judges with its innovative approach to cybersecurity.
^Group photo (from left to right): Prof. Lawrence K. YEUNG (Associate Dean (RPg) of Faculty of Engineering), Prof. Kaibin HUANG (Head of HKU EEE), Dr. Zhenglong LI, Mr. Songshi DOU, and Mr. Tianqin YANG, Dr. Vincent W.L. TAM (Principal Lecturer of HKU EEE).
^Congratulations to our student team for winning the IET YPEC 2025 award!
Project Description:
Cyberattacks are unauthorised behaviours aimed at illegally collecting user information or damaging the operational systems of enterprises and governments. The objective of this project is to identify any abnormal behaviour in network traffic to prevent the devices from being attacked. The resulting system is called the CoFi-IDS (Coarse-to-Fine grained Intrusion Detection System) as a two-stage framework in which it will firstly learn the representation of packets at different granularities (i.e. both coarse-grained and fine-grained information). At the second stage, the CoFi-IDS will try to identify any abnormal packets based on the learned features. The obtained empirical results revealed that the proposed CoFi-IDS is very effective in detecting both coarse-grained and fine-grained attack types when compared to other existing methods, such as the DCN and MLP approaches.
This recognition highlights the team’s dedication to advancing cybersecurity technologies and reflects the high caliber of research conducted at HKU Engineering. We extend our heartfelt congratulations to the student team and their supervisors for this outstanding achievement and look forward to their continued success.
Learn more about the IET YPEC Award: https://www.ietypec.org