Li, Jun

Federated Learning With Differential Privacy: Algorithms and Performance Analysis

Wei, K., Li, J., Ding, M., Ma, C., Yang, H. H., Farokhi, F., Jin, S., Quek, T. Q. S., & Vincent Poor, H. (2020) · IEEE Transactions on Information Forensics and Security

Privacy-Preserving Technologies in DataStochastic Gradient Optimization Techniques

Cited by 2,400

Federated learning meets blockchain in edge computing: Opportunities and challenges

Nguyen, D. C., Ding, M., Pham, Q.-V., Pathirana, P. N., Le, L. B., Seneviratne, A., Li, J., Niyato, D., & Poor, H. V. (2021) · IEEE Internet of Things Journal

Privacy-Preserving Technologies in DataIoT and Edge/Fog Computing

Cited by 661

On Safeguarding Privacy and Security in the Framework of Federated Learning

Ma, C., Li, J., Ding, M., Yang, H. H., Shu, F., Quek, T. Q. S., & Poor, H. V. (2020) · IEEE Network

Privacy-Preserving Technologies in DataCloud Data Security Solutions

Cited by 318

When Federated Learning Meets Blockchain: A New Distributed Learning Paradigm

Ma, C., Li, J., Ding, M., Shi, L., Wang, T., Han, Z., & Poor, H. V. (2020) · arXiv

Privacy-Preserving Technologies in DataBlockchain Technology Applications and Security

Cited by 225

Federated Learning for Industrial Internet of Things in Future Industries

Nguyen, D. C., Ding, M., Pathirana, P. N., Seneviratne, A., Li, J., Niyato, D., & Poor, H. V. (2021) · IEEE Wireless Communications

Privacy-Preserving Technologies in DataIoT and Edge/Fog Computing

Cited by 166

Low-Latency Federated Learning Over Wireless Channels With Differential Privacy

Wei, K., Li, J., Ma, C., Ding, M., Chen, C., Jin, S., Han, Z., & Poor, H. V. (2022) · IEEE Journal on Selected Areas in Communications

Privacy-Preserving Technologies in DataIoT and Edge/Fog Computing

Cited by 109

Trusted AI in Multiagent Systems: An Overview of Privacy and Security for Distributed Learning

Ma, C., Li, J., Wei, K., Liu, B., Ding, M., Yuan, L., Han, Z., & Vincent Poor, H. (2023) · Proceedings of the IEEE

Privacy-Preserving Technologies in DataAdversarial Robustness in Machine Learning

Cited by 96