Blockchain-Based Lightweight Authentication Mechanisms for Industrial Internet of Things and Information Systems

Blockchain-Based Lightweight Authentication Mechanisms for Industrial Internet of Things and Information Systems

Mingrui Zhao, Chunjing Shi, Yixiao Yuan
Copyright: © 2024 |Pages: 30
DOI: 10.4018/IJSWIS.334704
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Abstract

The industrial internet of things (IIoT) necessitates robust cross-domain authentication to secure sensitive on-site equipment data. This paper presents a refined reputation-based lightweight consensus mechanism (LRBCM) tailored for IIoT's distributed network structures. Leveraging node reputation values, LRBCM streamlines ledger consensus, minimizing communication overhead and complexity. Comparative experiments show LRBCM outperforms competing mechanisms. It maintains higher throughput as the number of participating nodes increases and achieves a throughput approximately 10.78% higher than ReCon. Moreover, runtime analysis demonstrates LRBCM's scalability, surpassing ReCon by approximately 12.79% with equivalent nodes and transactions. In addition, as a combination of LRBCM, the proposed distributed lightweight authentication mechanism (ELAM) is rigorously evaluated against the security of various attacks, and its resilience is confirmed. Experiments show that ELAM has good efficiency while maintaining high security.
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1. Introduction

The internet of things (IoT) represents the concept of intelligent interaction, seamlessly connecting objects through intercommunication and information exchange. The industrial internet of things (IIoT) applies IoT technology to industrial production, integrating physical devices, sensors, and cloud computing to monitor, control, and optimize industrial processes (Sisinni et al., 2018; Sharma and Sharma, 2022; Yang et al., 2017; Hassija et al., 2019; Yao et al., 2021). In the modern industrial domain, IIoT has become an indispensable part, offering rich opportunities for machine-to-machine communication and automation. However, as devices and sensors become increasingly connected to networks, ensuring the authentication and data integrity of these devices is crucial (Mukherjee and Biswas, 2018; Wang et al., 2022; Nashwan, 2021; Raj and Prakash, 2022; Sengupta et al., 2020; Wang et al., 2019; Feng and Wang, 2022; Danish et al., 2020; Gupta et al., 2021). In the realm of IIoT security and authentication mechanisms, robust authentication mechanisms are urgently needed to protect industrial systems from malicious attacks and unauthorized access.

In recent years, numerous studies have focused on addressing security and authentication challenges in industrial IoT (Chen et al., 2021; Zhuang et al., 2019; Yuan et al., 2021; Yang et al., 2018; Pan et al., 2022; Shen et al., 2020; Esfahani et al., 2017; Xiong et al., 2020; Sadhukhan et al., 2021; Khalid et al., 2020; Stergiou et al., 2021; Wang et al., 2022; Mishra et al., 2022; Wang et al., 2019; Mohammadipanah and Sajedi, 2021; Fu et al., 2022). For example, research in machine-to-machine (M2M) communication has demonstrated outstanding performance compared to traditional methods (Nguyen et al., 2021). The rise of artificial intelligence and machine learning has also led to the proposal of various methods for detecting and preventing malicious software attacks (Zhang et al., 2023; Ling and Hao, 2022; Tembhurne et al., 2022; Xu et al., 2021; Gaurav et al., 2023; Lu et al., 2021; Ling and Hao, 2022; Sharma and Sharma, 2022; Devi and Bharti, 2022; Singh and Gupta, 2022).

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