Blockchain-Enabled 5G Edge Networks and Beyond: An Intelligent Cross-Silo Federated Learning Approach. (28th March 2021)

• Record Type: Journal Article
• Authors: Rahmadika, Sandi; Firdaus, Muhammad; Jang, Seolah; Rhee, Kyung-Hyune
• Other Names: Wang Jinwei Academic Editor.
• Is Part Of: Security and communication networks. Volume 2021(2021)
• Publication Date: 2021-03-28
• Subjects: Computer networks -- Security measures -- Periodicals; Computer security -- Periodicals; Cryptography -- Periodicals; 005.805
• DOI: 10.1155/2021/5550153
• Languages: English
• ISSNs: 1939-0114

Abstract

Abstract : Edge networks (ENs) in 5G have the capability to protect traffic between edge entry points (edge-to-edge), enabling the design of various flexible and customizable applications. The advantage of edge networks is their pioneering integration of other prominent technologies such as blockchain and federated learning (FL) to produce better services on wireless networks. In this paper, we propose an intelligent system integrating blockchain technologies, 5G ENs, and FL to create an efficient and secure framework for transactions. FL enables user equipment (UE) to train the artificial intelligence model without exposing the UE's valuable data to the public, or to the model providers. Furthermore, the blockchain is an immutable data approach that can be leveraged for FL across 5G ENs and beyond. The recorded transactions cannot be altered maliciously, and they remain unchanged by design. We further propose a dynamic authentication protocol for UE to interact with a diverse base station. We apply blockchain as a reward mechanism in FL to enable computational offloading in wireless networks. Additionally, we implement and investigate blockchain technology for FL in 5G UE.