Privacy-Preserving Machine Learning / SpringerBriefs on Cyber Security Systems and Networks (PDF)
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This book provides a thorough overview of the evolution of privacy-preserving machine learning schemes over the last ten years, after discussing the importance of privacy-preserving techniques. In response to the diversity of Internet services, data services based on machine learning are now available for various applications, including risk assessment and image recognition. In light of open access to datasets and not fully trusted environments, machine learning-based applications face enormous security and privacy risks. In turn, it presents studies conducted to address privacy issues and a series of proposed solutions for ensuring privacy protection in machine learning tasks involving multiple parties. In closing, the book reviews state-of-the-art privacy-preserving techniques and examines the security threats they face.
Ping Li was born in May 1985 in Baojing Country of Hunan Province. She received her Ph.D. in School of Mathematics at Sun Yat-Sen University in June 2016 (Supervisor Prof. Zheng-An Yao) and joined the Guangzhou University as a postdoctoral fellow from July 2016 to December 2018 (Co-Supervisor Prof. Jin Li). Currently, she works at South China Normal University (Youth Talent). Her research fields are applied cryptography, cloud computing security, and privacy-preserving machine learning. Her current research direction contains cryptographic technologies, storage security and computation security in cloudcomputing,
Zheli Liu received the B.Sc. and M.Sc. degrees in computer science from Jilin University, China, in 2002 and 2005, respectively. He received the Ph.D. degree in computer application from Jilin University in 2009. After a postdoctoral fellowship in Nankai University, he joined the College of Cyber Science of Nankai University in 2011. Currently, he works at Nankai University as an associate professor. His current research interests include applied cryptography and data privacy protection.
Xiaofeng Chen received his B.S. and M.S. in Mathematics from Northwest University, China, in 1998 and 2000, respectively. He got his Ph.D. degree in Cryptography from Xidian University in 2003. Currently, he works at Xidian University as a professor. His research interests include applied cryptography and cloud computing security. He has published over 100 research papers in refereed international conferences and journals. His work has been cited more than 4000 times at Google Scholar. He is in the Editorial Board of IEEE Transactions on Dependable and Secure Computing (IEEE TDSC), Security and Communication Networks (SCN), and Computing and Informatics (CAI), etc. He has served as the program/general chair or program committee member in over 30 international conferences.
Tong Li received his B.S. and M.S. from Taiyuan University of Technology and Beijing University of Technology, in 2011 and 2014, respectively, both in Computer Science & Technology. He got his Ph.D. degree in information security from Nankai University at 2017. After a postdoctoral fellowship in Guangzhou University, he currently is an associate professor in Nankai University. His research interests include applied cryptography and data privacy protection in cloud computing.
- Autoren: Jin Li , Ping Li , Zheli Liu , Xiaofeng Chen , Tong Li
- 2022, 1st ed. 2022, 88 Seiten, Englisch
- Verlag: Springer Nature Singapore
- ISBN-10: 9811691398
- ISBN-13: 9789811691393
- Erscheinungsdatum: 14.03.2022
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