A survey on federated unlearning: challenges, methods, and future directions

• Main Authors: Liu, Ziyao, Jiang, Yu, Shen, Jiyuan, Peng, Minyi, Lam, Kwok-Yan, Yuan, Xingliang, Liu, Xiaoning
• Other Authors: College of Computing and Data Science
• Format: Article
• Language: English
• Published: 2025
• Subjects: Computer and Information Science; Federated unlearning; Digital trust
• Online Access: https://hdl.handle.net/10356/182536
• Institution: Nanyang Technological University

In recent years, the notion of ``the right to be forgotten" (RTBF) has become a crucial aspect of data privacy for digital trust and AI safety, requiring the provision of mechanisms that support the removal of personal data of individuals upon their requests. Consequently, machine unlearning (M...