Securing federated learning: a covert communication-based approach
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...
Main Authors: | Xie, Yuan-Ai, Kang, Jiawen, Niyato, Dusit, Nguyen, Thi Thanh Van, Nguyen, Cong Luong, Liu, Zhixin, Yu, Han |
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Other Authors: | College of Computing and Data Science |
Format: | Journal Article |
Language: | English |
Published: |
2024
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Subjects: | |
Online Access: | https://hdl.handle.net/10356/179061 |
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