Securing federated learning: a covert communication-based approach

• Main Authors: Xie, Yuan-Ai, Kang, Jiawen, Niyato, Dusit, Nguyen, Thi Thanh Van, Nguyen, Cong Luong, Liu, Zhixin, Yu, Han
• Other Authors: College of Computing and Data Science
• Format: Article
• Language: English
• Published: 2024
• Subjects: Computer and Information Science; Artificial intelligence; Federated learning
• Online Access: https://hdl.handle.net/10356/179061
• Institution: Nanyang Technological University

Federated Learning Networks (FLNs) have been envisaged as a promising paradigm to collaboratively train models among mobile devices without exposing their local privacy data. Due to the need for frequent model updates via wireless links, FLNs are vulnerable to various attacks (e.g., eavesdropping at...