Blockchain-Enabled 5G Edge Networks and Beyond: An Intelligent Cross-Silo Federated Learning Approach

被引:20
|
作者
Rahmadika, Sandi [1 ]
Firdaus, Muhammad [1 ]
Jang, Seolah [1 ]
Rhee, Kyung-Hyune [2 ]
机构
[1] Pukyong Natl Univ, Dept Artificial Intelligence Convergence, Busan 48513, South Korea
[2] Pukyong Natl Univ, Dept IT Convergence & Applicat Engn, Busan 48513, South Korea
基金
新加坡国家研究基金会;
关键词
INDUSTRIAL INTERNET;
D O I
10.1155/2021/5550153
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
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.
引用
收藏
页数:14
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