Privacy-preserving aggregation in federated learning: a survey

• Main Authors: Liu, Ziyao, Guo, Jiale, Yang, Wenzhuo, Fan, Jiani, Lam, Kwok-Yan, Zhao, Jun
• Other Authors: School of Computer Science and Engineering
• Format: Article
• Language: English
• Published: 2023
• Subjects: Engineering::Computer science and engineering; Computational Modeling; Cryptography
• Online Access: https://hdl.handle.net/10356/164430
• Institution: Nanyang Technological University

Over the recent years, with the increasing adoption of Federated Learning (FL) algorithms and growing concerns over personal data privacy, Privacy-Preserving Federated Learning (PPFL) has attracted tremendous attention from both academia and industry. Practical PPFL typically allows multiple partici...