CityU

Associate Professor (research) Dayong Ye


Dr. Dayong Ye

Associate professor(research), doctoral supervisor/master supervisor 

Email：dyye@cityu.edu.mo

Tel: (853)85902336
Office address:  Room S504, Stanley Ho Building, City University of Macau (Taipa)

 

Educational qualifications 

2013 PhD in Computer Science, University of Wollongong, Australia

2009 Master of Computer Science by Research, University of Wollongong,Australia

2003 Bachelor of Engineering, Hefei University of Technology, China

 

Current Position

Associate Professor(research) of Data Science, City University of Macau

 

Research Interests

Privacy in Artificial Intelligence, Multi-Agent System Security

 

Research & Publications

  1. Dayong Ye, T Zhu, F He, B Liu, M Xue and W Zhou, “Cross-Modal Prompt Inversion: Unifying Threats to Text and Image Generative AI Models”, Proc. of USENIX Security Symposium, 2025. (CCF A)
  2. Dayong Ye, T Zhu, S Wang, B Liu, L Y Zhang, W Zhou and Y Zhang, “Data-Free Model-Related Attacks: Unleashing the Potential of Generative AI”, Proc. of USENIX Security Symposium, 2025. (CCF A)
  3. Dayong Ye, T Zhu, J Li, K Gao, B Liu, L Y Zhang, W Zhou and Y Zhang, “Data Duplication: A Novel Multi-Purpose Attack Paradigm in Machine Unlearning”, Proc. of USENIX Security Symposium, 2025. (CCF A)
  4. Dayong Ye, T Zhu, C Zhu, D Wang, K Gao, Z Shi, S Shen, W Zhou and M Xue, “Reinforcement Unlearning”, Proc. of NDSS Symposium, 2025. (CCF A)
  5. Dayong Ye, H Chen, S Zhou, T Zhu, W Zhou, S Ji, “Model Inversion Attack Against Transfer Learning: Inverting a Model Without Querying It”, IEEE Transactions on Dependable and Secure Computing, 2025. (CCF A, JCR Q1)
  6. Dayong Ye, T Zhu, K Gao, C Zhu, and W Zhou, “Cooperating or Kicking Out: Defending against Poisoning Attacks in Federated Learning via the Evolution of Cooperation”, IEEE Transactions on Dependable and Secure Computing, 2025. (CCF A, JCR Q1)
  7. Dayong Ye, T Zhu, K Gao and W Zhou, “Defending against Label-only Attacks via Meta-Reinforcement Learning”, IEEE Transactions on Information Forensics and Security, 2024. (CCF A, JCR Q1)
  8. T Zhu, Dayong Ye, Z Cheng, W Zhou, S Y Philip, “Learning Games for Defending Advanced Persistent Threats in Cyber Systems”, IEEE Transactions on Systems, Man, and Cybernetics: Systems, vol. 53, no. 4, pp. 2410-2422, 2023. (JCR Q1)
  9. T Zhu, Dayong Ye, S Zhou, B Liu, W Zhou, “Label-only Model Inversion Attacks: Attack with the Least Information”, IEEE Transactions on Information Forensics and Security, vol. 18, pp. 991-1005, 2023. (CCF A, JCR Q1)
  10. Dayong Ye, T Zhu, C Zhu, W Zhou, SY Philip, “Model-Based Self-Advising for Multi-Agent Learning”, IEEE Transactions on Neural Networks and Learning Systems, vol. 34, no. 10, pp. 7934-7945, 2023. (JCR Q1)
  11. Dayong Ye, S Shen, T Zhu, B Liu, W Zhou, “One Parameter DefenseDefending Against Data Inference Attacks via Differential Privacy”, IEEE Transactions on Information Forensics and Security, vol. 17, pp.1466-1480, 2022. (CCF A, JCR Q1)
  12. Dayong Ye, T Zhu, Z Cheng, W Zhou and P S Yu, “Differential Advising in Multi-Agent Reinforcement Learning”, IEEE Transactions on Cybernetics, vol. 52, no. 6, pp. 5508-5521, 2022. (JCR Q1)
  13. Dayong Ye, T Zhu, S Shen, W Zhou and P S Yu,“Differentially Private Multi-Agent Planning for Logistic-like Problems”, IEEE Transactions on Dependable and Secure Computing, vol. 19, pp. 1212-1226, 2022. (CCF A, JCR Q1)
  14. T Zhu, Dayong Ye, W Wang, W Zhou and P S Yu, “More Than Privacy: Applying Differential Privacy in Key Areas of Artificial Intelligence”, IEEE Transactions on Knowledge and Data Engineering, vol. 14, no.6, pp. 2824-2843, 2022. (CCF A, JCR Q1)
  15. S Wang, T Zhu, Dayong Ye, W Zhou, “When machine unlearning meets retrieval-augmented generation (rag): Keep secret or forget knowledge?”, IEEE Transactions on Dependable and Secure Computing, 2025. (CCF A, JCR Q1)
  16. S Wang, T Zhu, B Liu, M Ding, Dayong Ye, W Zhou, P Yu, “Unique security and privacy threats of large language models: A comprehensive survey”, ACM Computing Surveys, vol. 58, no. 4, pp. 1-36, 2025. (CCF A, JCR Q1)
  17. S Zhou, Dayong Ye, T Zhu, W Zhou, “Defending Against Neural Network Model Inversion Attacks via Data Poisoning”, IEEE Transactions on Neural Networks and Learning Systems, 2025. (JCR Q1)
  18. S Zhou, T Zhu, Dayong Ye, X Yu and W Zhou, “Boosting Model Inversion Attacks with Adversarial Examples”, IEEE Transactions on Dependable and Secure Computing, 2023. (CCF A, JCR Q1)
  19. C Zhu, Z Cheng, Dayong Ye, FK Hussain, T Zhu, and W Zhou, “Time-driven and Privacy-preserving Navigation Model for Vehicle-to-vehicle Communication Systems”, IEEE Transactions on Vehicular Technology, 2023.(JCR Q1)
  20. S Zhou, C Liu, Dayong Ye, T Zhu, W Zhou, P S Yu, “Adversarial attacks and defenses in deep learning: From a perspective of cybersecurity”, ACM Computing Surveys, vol. 55, no. 8, pp. 1-39, 2022. (CCF A, JCR Q1)
  21. L Zhang, T Zhu, F K Hussain, Dayong Ye, and W Zhou, “A Game-theoretic Method for Defending against Advanced Persistent Threats in Cyber Systems”, IEEE Transactions on Information Forensics and Security,2022. (CCF A, JCR Q1)

 

Achievement

2012 Chinese Government Award for Outstanding Self-Financed Students Abroad