DRL-Based Secure Aggregation and Resource Orchestration in MEC-Enabled Hierarchical Federated Learning

• Published in: IEEE internet of things journal Vol. 10; no. 20; p. 1
• Main Authors: Zhao, Tantan, Li, Fan, He, Lijun
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 15.10.2023; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Computational modeling; Cybersecurity; Data models; Deep reinforcement learning; Edge computing; Federated learning; hierarchical federated learning; Internet of Things; Mixed integer; Mobile computing; mobile edge computing; Optimization; resource orchestration; secure aggregation; Security; Servers; Training; Training data

Federated learning (FL) provides a new paradigm for protecting data privacy by enabling model training at devices and model aggregation at servers. However, data information may be leaked to honest-but-curious aggregation servers by updated model parameters. The existing secure methods do not fully...