Blockchain-empowered federated learning approach for an intelligent and reliable D2D caching scheme

Cheng, R. , Sun, Y. , Liu, Y., Xia, L. , Feng, D. and Imran, M. A. (2022) Blockchain-empowered federated learning approach for an intelligent and reliable D2D caching scheme. IEEE Internet of Things Journal, 9(11), pp. 7879-7890. (doi: 10.1109/JIOT.2021.3103107)

Abstract

Cache-enabled device-to-device (D2D) communication is a potential approach to tackle the resource shortage problem. However, public concerns of data privacy and system security still remain, which thus arises an urgent need for a reliable caching scheme. Fortunately, federated learning (FL) with a distributed paradigm provides an effective way to privacy issue by training a high-quality global model without any raw data exchanges. Besides privacy issue, blockchain can be further introduced into FL framework to resist the malicious attacks occurred in D2D caching networks. In this study, we propose a double-layer blockchain-based deep reinforcement FL (BDRFL) scheme to ensure privacy-preserved and caching-efficient D2D networks. In BDRFL, a double-layer blockchain is utilized to further enhance data security. Simulation results first verify the convergence of BDRFL-based algorithm, and then demonstrate that the download latency of the BDRFL-based caching scheme can be significantly reduced under different types of attacks when compared with some existing caching policies.

• Item Type: Articles
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Xia, Le and Imran, Professor Muhammad and Sun, Dr Yao and CHENG, RUNZE
• Authors: Cheng, R., Sun, Y., Liu, Y., Xia, L., Feng, D., and Imran, M. A.
• College/School: College of Science and Engineering > School of Engineering > Systems Power and Energy; College of Science and Engineering > School of Engineering > Autonomous Systems and Connectivity
• Journal Name: IEEE Internet of Things Journal
• Publisher: IEEE
• ISSN: 2372-2541
• ISSN (Online): 2327-4662
• Published Online: 06 August 2021
• Copyright Holders: Copyright © 2021 IEEE
• First Published: First published in IEEE Internet of Things Journal 9(11): 7879-7890
• Publisher Policy: Reproduced under a Creative Commons Licence

Project Code	Award No	Project Name	Principal Investigator	Funder's Name	Funder Ref	Lead Dept
300725		Distributed Autonomous Resilient Emergency Management System (DARE)	Muhammad Imran	Engineering and Physical Sciences Research Council (EPSRC)	EP/P028764/1	ENG - Systems Power & Energy