Securing federated learning: a covert communication-based approach

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...

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Bibliographic Details
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: Journal Article
Language:English
Published: 2024
Subjects:
Computer and Information Science
Artificial intelligence
Federated learning
Online Access:https://hdl.handle.net/10356/179061

Internet

https://hdl.handle.net/10356/179061

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