Alumni Current Students Lecturers Staff

Institute of Cyberspace Technology | Academic Staff

Prof. QU Bo

BSc, MSc (Shanghai Jiao Tong University); PhD (Delft University of Technology)

Associate Dean, Institute of Cyberspace Technology

Certified Information Security Professional (CISP)
Certified Information Security Instructor (CISI)

Teaching Area: Cyberspace Security, Network Security, Artificial Intelligence Applications in Cybersecurity, Complex Networks

Prof. Bo QU is Associate Dean of the Institute of Cyberspace Technology at HKCT Institute of Higher Education. He received his BSc in Information Security and MSc in Computer Science from Shanghai Jiao Tong University in 2009 and 2012 respectively, and obtained his PhD in Intelligent Systems from Delft University of Technology in 2017. Before joining HKCT, he worked in applied network security research at Tencent Technology and later served as a research associate at Peng Cheng Laboratory. His research focuses on cyberspace security, complex networks, network analysis and network representation learning. His recent work covers encrypted traffic classification, anomaly detection, edge-network security, and diffusion or epidemic dynamics on complex networks. In addition to research and teaching, Prof. Qu has contributed to professional practice by serving as a judge for cybersecurity defence exercises such as “Yuedun” and “Shenlan”, and by organising regional rounds of national-level cybersecurity competitions. He is also recognised as a Shenzhen Peacock Plan Talent. At HKCT, he contributes to academic development, research initiatives, and cybersecurity talent cultivation in both higher education and applied professional training.

Cyberspace Security, Network Security, Encrypted Traffic Classification, Network Representation Learning, Complex Networks, Anomaly Detection, Information Diffusion and Epidemic Dynamics on networks

Selected Publications

Journal Articles

Kuang, Z., Qu, B., Li, X., & Li, C. (2025). Balancer: Temporal Knowledge Graph Embedding for Novel Events Reasoning with Contrastive Learning. Knowledge-Based Systems, 114984.

Wang, W., Li, C., Qu, B. and Li, X. (2024). Predicting epidemic threshold in complex networks by graph neural network. Chaos: An Interdisciplinary Journal of Nonlinear Science.

Liu, Y., Wang, X., Qu, B. and Zhao, F. (2024). ATVITSC: A Novel Encrypted Traffic Classification Method Based on Deep Learning. IEEE Transactions on Information Forensics and Security.

Li, C., Shi, M., Qu, B. and Li, X. (2022). Deep Attributed Network Representation Learning via Attribute Enhanced Neighborhood. Neurocomputing.

Liu, L., Qu, B., Chen, B., Hanjalic, A., & Wang, H. (2018). Modelling of information diffusion on social networks with applications to WeChat. Physica A: Statistical Mechanics and its Applications, 496, 318-329.

Conference Papers

Yi, C., Qu, B., & Kwok, L. F. (2025, November). From Higher Diploma to Master: A Smart-Tech Vertical Curriculum Framework in Cyber Technology Education. In International Conference on Technology in Education (pp. 340-351). Singapore: Springer Nature Singapore.

Qu, B., Wang, W., Li, C., & Li, X. (2025, August). Predicting Dynamics on Hypergraphs with Graph Attention Networks. In 2025 8th International Conference on Big Data and Artificial Intelligence (BDAI) (pp. 197-201). IEEE.

Hu, Z., Qu, B., Li, X. and Li, C. (2024). An Encrypted Traffic Classification Framework Based on Higher-Interaction-Graph Neural Network. Australasian Conference on Information Security and Privacy (ACISP 2024).

Zhou, Z., Li, C., Qu, B., & Li, X. (2024, May). Predicting higher-order dynamics without network topology by ridge regression. In 2024 IEEE International Symposium on Circuits and Systems (ISCAS) (pp. 1-5). IEEE.

Qu, B., & Wang, H. (2016, November). The accuracy of mean-field approximation for susceptible-infected-susceptible epidemic spreading with heterogeneous infection rates. In International Workshop on Complex Networks and their Applications (pp. 499-510). Cham: Springer International Publishing.

Research Grants

2025/26 Inter-Institutional Development Scheme (IIDS)
Project Title: Application and Challenges of Blockchain Technology in Cross-Border Data Security: Practices and Prospects (UGC/IIDS21/E01/25)

Honours and Awards

Guangdong Electronic Information Industry Science and Technology Award (Ranked 4/14), Guangdong Institute of Electronics (2024)

Industry-Education Integration Course Award (Individual Award), The 12th Internet Security Conference (ISC) (2024)

Guangdong Provincial Funding for Medium- and Long-term Overseas Training of Young Scientific and Technological Talents, Department of Science and Technology of Guangdong Province (2022)

Pilot Talent (Linghang Talent) (Individual Award), Nanshan District Government (Shenzhen) (2019)

Peacock Plan Talent (Individual Award), Shenzhen Municipal People’s Government (2018)