Privacy and robustness in federated learning: attacks and defenses

• Main Authors: Lyu, Lingjuan, Yu, Han, Ma, Xingjun, Chen, Chen, Sun, Lichao, Zhao, Jun, Yang, Qiang, Yu, Philip S.
• Other Authors: School of Computer Science and Engineering
• Format: Article
• Language: English
• Published: 2023
• Subjects: Engineering::Computer science and engineering; Federated Learning; Privacy
• Online Access: https://hdl.handle.net/10356/164531
• Institution: Nanyang Technological University

As data are increasingly being stored in different silos and societies becoming more aware of data privacy issues, the traditional centralized training of artificial intelligence (AI) models is facing efficiency and privacy challenges. Recently, federated learning (FL) has emerged as an alternative...