Bui Duc Manh

About Me

I’m currently a Ph.D. Candidate at University of Technology Sydney (UTS), Australia, where I work within 5G/6G Wireless Communications and IoT Networking Lab, specifically as part of the AI for Mobile Edge Networks (AI4MEN) Group, under the supervision of Prof. Hoang Dinh and Prof. Diep Nguyen.

Before this, I spent some time at Nanyang Technological University (NTU), Singapore, working as a Research Associate.

In 2025, I received my M.Sc. research degree from UTS, working within the same research group and supervision as my current PhD study. Before that, in 2023, I obtained my B.Sc. degree in electronics and communication engineering from the Vietnam National University-University of Engineering and Technology (VNU-UET), Vietnam, supervised by Dr. Tran Thi Thuy Quynh.

Research Interests

Recently, I’ve been working on Privacy-Preserving Deep Learning, focusing on integrating Homomorphic Encryption (HE) and Secure Multi-party Computation (SMPC) to emerging deep learning models. Alongside this, I have a strong interest in fundamental deep learning, particularly on Reinforcement Learning and Language Models from a deeper theoretical perspective.

News

• [May. 2025] I start to work in the BioRAI Lab, EEE, NTU as a Research Associate.
• [Jan. 2025] Our paper “Privacy-Preserving Cyberattack Detection in Blockchain-Based IoT Systems Using AI and Homomorphic Encryption” is accepted to the IEEE Internet of Things Journal (Q1, IF=8.2).
• [Dec. 2024] I successfully defended my M.Sc. thesis, entitled “Advanced Machine Learning for Privacy-Preserving Intrusion Detection in IoT Networks”.
• [Jul. 2024] Our paper “Homomorphic Encryption-Enabled Federated Learning for Privacy-Preserving Intrusion Detection in Resource-Constrained IoV Networks” is accepted to the IEEE Vehicular Technology Conference-Fall, Otc. 2024 (VTC2024-Fall).
• [Sep. 2023] I start my M.Sc. research journey at UTS.

Selected Publications

Professional Services

Reviewers

• IEEE Transactions on Mobile Computing (TMC), 2025
• IEEE Communications Magazine (COMMAG), 2025

Teaching

• Tutor (Lab Instructor) for IoT Security (42037), UTS, 2024-2025
• Tutor (Lab Instructor) for Cybersecurity for Mobile Platforms (42036), UTS, 2024

All Publications

Preprints

• [P2] B. D. Manh et al. "Mind Meets Space: Rethinking Agentic Spatial Intelligence from a Neuroscience-inspired Perspective," 2025 [arxiv].

• [P1] N. V. Duc , B. D. Manh, Q. T. Luu, D. T. Hoang, N. V. Linh, and D. N. Nguyen, "Secure and Efficient UAV-Based Face Detection via Homomorphic Encryption and Edge Computing," 2025 [arxiv].

Theses

• Master's Thesis, "Advanced Machine Learning for Privacy-Preserving Intrusion Detection in IoT Networks," 2025 [pdf].

Journals

• [J2] M. A. Hassan, M. B. Jamshidi, B. D. Manh, N. H. Chu, C. H. Nguyen, N. Q. Hieu, C. T. Nguyen, D. T. Hoang, D. N. Nguyen, N. V. Huynh, M. A. Alsheikh, and E. Dutkiewicz, "Enabling Technologies for Web 3.0: A Comprehensive Survey," Elsevier Computer Networks (accepted) (IF=4.4, Q1) [arxiv].

• [J1] B. D. Manh, C. H. Nguyen, D. T. Hoang, D. N. Nguyen, M. Zeng, and Q. V. Pham, "Privacy-preserving cyberattack detection in blockchain-based IoT systems using Ai and Homomorphic Encryption," IEEE Internet of Things Journal , vol. 12, no. 11, pp. 16478-16492, June 2025 (IF=8.9, Q1) [link] [arxiv].

Conferences

• [C4] C. H. Nguyen^*, B. D. Manh^*, D. T. Hoang, D. N. Nguyen, and L. Wang "PP-AICloud: Edge-Assisted Privacy-Preserving AI Inference with Homomorphic Encryption for Cloud-Based Mobile Services," In Proceedings of The 31st Annual International Conference On Mobile Computing And Networking (ACM MobiCom '25), Accepted 2025 (*:equal contribution).

• [C3] B. D. Manh, C. H. Nguyen, D. T. Hoang, and D. N. Nguyen, "Homomorphic Encryption-Enabled Federated Learning for Privacy-Preserving Intrusion Detection in Resource-Constrained IoV Networks," IEEE Vehicular Technology Conference, October 2024, Washington DC, USA.

• [C2] C. H. Nguyen, B. D. Manh, D. T. Hoang, D. N. Nguyen, and E. Dutkiewicz, "Towards Secure AI-empowered Vehicular Networks: A Federated Learning Approach using Homomorphic Encryption," IEEE Vehicular Technology Conference, October 2024, Washington DC, USA.

• [C1] D. H. Son, B. D. Manh, T. V. Khoa, N. L. Trung, D. T. Hoang, H. T. Minh, Y. Alem and L. Q. Minh, "Semi-Supervised Learning for Anomaly Detection in Blockchain-based Supply Chains," IEEE International Symposium on Communications and Information Technologies , September 2024, Bangkok, Thailand.

Book Chapters

• [B2] B. D. Manh, N. Q. Hieu, D. T. Hoang, D. N. Nguyen, and E. Hossain, "Machine Learning or Cyber-Attack Detection in IoT Networks: An Overview," Advanced Machine Learning for Cyber-Attack Detection in IoT Networks, 2025 [link].

• [B1] N. Q. Hieu, B. D. Manh, D. T. Hoang, D. N. Nguyen, and E. Hossain, "Challenges and Potential Research Directions for Machine Learning-based Cyber-Attack Detection in IoT Networks," Advanced Machine Learning for Cyber-Attack Detection in IoT Networks, 2025 [link].

Mentors

In addition to the guidance from my supervisors, I’ve had the opportunity to learn from and work with the following mentors:

• Dr. Nguyen Quang Hieu – research advisor during my time at UTS
• Dr. Chi-Hieu Nguyen – technical advisor on Homomorphic Encryption during my research at UTS
• Ph.D. Candidate Do Hai Son – main mentor during my undergraduate study at VNU-UET

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