Federated Learning-Based Resource Management with Blockchain Trust Assurance in Smart IoT

Author:

Fu Xiuhua1,Peng Rongqun12ORCID,Yuan Wenhao12,Ding Tian1,Zhang Zhe1,Yu Peng2ORCID,Kadoch Michel3ORCID

Affiliation:

1. School of Computer Science and Technology, Shandong University of Technology, Zibo 255000, China

2. State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing 100876, China

3. Department of Electrical Engineering, ETS, University of Quebec, Montreal, QC H3C 3J7, Canada

Abstract

Resource management is a key issue that needs to be addressed in the future smart Internet of Things (IoT). This paper focuses on a Federated Learning (FL)-based resource management mechanism in IoT. It incorporates blockchain technology to guarantee the security of the FL model parameters exchange. We propose an IoT resource management framework incorporating blockchain and federated learning technologies; then, a specific FL-based resource management with a blockchain trust assurance algorithm is given. We use a Support Vector Machine (SVM) classifier to detect malicious nodes in order to avoid the impact on the performance of the FL-based algorithm. Finally, we perform simulation to verify the SVM classification effect and the proposed algorithm performance. The results show that the SVM-based malicious node identification accuracy can be acceptable. Moreover, the proposed algorithm obtains better performance when malicious nodes are excluded from the FL selected participant.

Funder

Open Foundation of State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications

Publisher

MDPI AG

Subject

Electrical and Electronic Engineering,Computer Networks and Communications,Hardware and Architecture,Signal Processing,Control and Systems Engineering

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