Security and Privacy in Federated Learning

In this book, the authors highlight the latest research findings on the security and privacy of federated learning systems. The main attacks and counterattacks in this booming field are presented to readers in connection with inference, poisoning, generative adversarial networks, differential privacy, secure multi-party computation, homomorphic encryption, and shuffle, respectively.

The book offers an essential overview for researchers who are new to the field, while also equipping them to explore this "uncharted territory." For each topic, the authors first present the key concepts, followed by the most important issues and solutions, with appropriate references for further reading.

The book is self-contained, and all chapters can be read independently. It offers a valuable resource for master's students, upper undergraduates, Ph.D. students, and practicing engineers alike.

Shui Yu 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 four monographs and edited two books, more than 500 technical papers, including top journals and top conferences, such as IEEE TPDS, TC, TIFS, TMC, TKDE, TETC, ToN, and INFOCOM. His h-index is 66. 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 served as a Distinguished Lecturer of IEEE Communications Society (2018-2021). He is a Distinguished Visitor of IEEE Computer Society, a voting member of IEEE ComSoc Educational Services board, and an elected member of Board of Governor of IEEE Vehicular Technology Society.

Lei Cui received his PhD degree from Deakin University, Australia, in 2021. He is now working as an associate research fellow at Shandong Computer Science Center (National Supercomputer Center in Jinan), China. He has authored or co-authored more than 30 publications, including monographs, book chapters, and journal and conference papers. Some of his publications have been published in top venues such as IEEE TII, IEEE TNSM, and IEEE TPDS. His research interests include security and privacy issues in IoT, social networks, and machine learning. Dr. Lei is active in the communication society and has served as a reviewer for many Q1 journals and a TPC Member for international conferences.

Shui Yu於2004年在澳大利亞的迪肯大學獲得博士學位。他目前是澳大利亞悉尼科技大學計算機科學學院的教授。Yu博士的研究興趣包括大數據、安全與隱私、網絡和數學建模。他已出版了四本專著和編輯了兩本書，發表了500多篇技術論文，包括IEEE TPDS、TC、TIFS、TMC、TKDE、TETC、ToN和INFOCOM等頂級期刊和頂級會議。他的h指數為66。Yu博士於2013年開創了大數據網絡研究領域，他的研究成果已被亞馬遜雲安全等工業系統廣泛應用。他目前擔任多個知名編輯委員會的成員，包括IEEE通信調查與教程（區域編輯）、IEEE通信雜誌、IEEE物聯網期刊等。他曾擔任IEEE通信學會的傑出講師（2018-2021年），是IEEE計算機學會的傑出訪問學者，IEEE ComSoc教育服務委員會的投票成員，以及IEEE車輛技術學會的理事會選舉成員。

Lei Cui於2021年在澳大利亞的迪肯大學獲得博士學位。他目前在中國山東省計算機科學中心（濟南國家超級計算機中心）擔任副研究員。他已經撰寫或合著了30多篇論文，包括專著、書籍章節以及期刊和會議論文。他的一些論文已發表在IEEE TII、IEEE TNSM和IEEE TPDS等頂級期刊上。他的研究興趣包括物聯網、社交網絡和機器學習中的安全和隱私問題。Lei博士在通信學會中非常活躍，並擔任多個Q1期刊的審稿人和國際會議的技術節目委員會成員。