报告题目：Security and Privacy in Federated Learning

报告人：Shui Yu，悉尼科技大学教授

报告时间：2021年7月5日 星期一 09:00

报告地点：腾讯会议ID: 957 254 201

报告摘要：

Federated Learning is a promising computing framework for numerous applications, and it has attracted a lot of attention in security and privacy perspectives. In this talk, we would like to offer an overview of the domain for audience. We will present the main branches in the field, including inferencing, poisoning, GAN, differential privacy, and homomorphic encryption. Hopefully, this talk will set a good starting point for interested researchers.

报告人简介:

Shui Yu (IEEE SM’12) obtained his PhD from Deakin University, Australia, in 2004. He currently is a Professor of School of Computer Science, University of Technology Sydney, Australia. Dr Yu’s research interest includes Big Data, Security and Privacy, Networking, and Mathematical Modelling. He has published three monographs and edited two books, more than 400 technical papers, including top journals and top conferences, such as IEEE TPDS, TC, TIFS, TMC, TKDE, TETC, ToN, and INFOCOM. His h-index is 54. Dr Yu initiated the research field of networking for big data in 2013, and his research outputs have been widely adopted by industrial systems, such as Amazon cloud security. He is currently serving a number of prestigious editorial boards, including IEEE Communications Surveys and Tutorials (Area Editor), IEEE Communications Magazine, IEEE Internet of Things Journal, and so on. He is a Senior Member of IEEE, a member of AAAS and ACM, and a Distinguished Lecturer of IEEE Communications Society.