Advancing Federated Learning in 6G: A Trusted Architecture with Graph-based Analysis

arXiv (Cornell University)

Abstract

Integrating native AI support into the network architecture is an essential objective of 6G. Federated Learning (FL) emerges as a potential paradigm, facilitating decentralized AI model training across a diverse range of devices under the coordination of a central server. However, several challenges hinder its wide application in the 6G context, such as malicious attacks and privacy snooping on local model updates, and centralization pitfalls. This work proposes a trusted architecture for supporting FL, which utilizes Distributed Ledger Technology (DLT) and Graph Neural Network (GNN), including three key features. First, a pre-processing layer employing homomorphic encryption is incorporated to securely aggregate local models, preserving the privacy of individual models. Second, given the distributed nature and graph structure between clients and nodes in the pre-processing layer, GNN is leveraged to identify abnormal local models, enhancing system security. Third, DLT is utilized to decentralize the system by selecting one of the candidates to perform the central server's functions. Additionally, DLT ensures reliable data management by recording data exchanges in an immutable and transparent ledger. The feasibility of the novel architecture is validated through simulations, demonstrating improved performance in anomalous model detection and global model accuracy compared to relevant baselines.

Authors 5

1. Wenxuan Ye
2. Chendi Qian

   Technical University of Munich

   Affiliation as printed

   Information and Technology , Technical University of Munich

3. Xueli An Aachen : Machine Learning and Reasoning

   Huawei Technologies (Germany) · RWTH Aachen University

   Affiliation as printed

   : Machine Learning and Reasoning , RWTH Aachen

   Advanced Wireless Technology Laboratory , Munich Research Center , Huawei Technologies Duesseldorf GmbH

4. Xueqiang Yan

   Huawei Technologies (China)

   Affiliation as printed

   Wireless Technology Lab , 2012 Laboratories , Huawei Technologies Co. , Ltd

5. Georg Carle

   Technical University of Munich

   Affiliation as printed

   TUM School of Computation,