基于区块链的工业物联网和信息系统轻量级认证机制

IF 4.1 4区 计算机科学 Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE International Journal on Semantic Web and Information Systems Pub Date : 2023-12-15 DOI:10.4018/ijswis.334704
Mingrui Zhao, Chunjing Shi, Yixiao Yuan
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引用次数: 0

摘要

工业物联网(IIoT)需要强大的跨域身份验证,以确保敏感的现场设备数据安全。本文针对 IIoT 的分布式网络结构,提出了一种经过改进的基于信誉的轻量级共识机制(LRBCM)。利用节点信誉值,LRBCM 简化了分类账共识,最大限度地减少了通信开销和复杂性。对比实验表明,LRBCM 优于其他竞争机制。随着参与节点数量的增加,它能保持更高的吞吐量,吞吐量比 ReCon 高出约 10.78%。此外,运行时分析表明了 LRBCM 的可扩展性,在节点和事务数量相当的情况下,LRBCM 比 ReCon 高出约 12.79%。此外,作为 LRBCM 的一种组合,所提出的分布式轻量级认证机制(ELAM)针对各种攻击的安全性进行了严格评估,其弹性得到了证实。实验表明,ELAM 在保持高安全性的同时还具有良好的效率。
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Blockchain-Based Lightweight Authentication Mechanisms for Industrial Internet of Things and Information Systems
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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来源期刊
CiteScore
6.20
自引率
12.50%
发文量
51
审稿时长
20 months
期刊介绍: The International Journal on Semantic Web and Information Systems (IJSWIS) promotes a knowledge transfer channel where academics, practitioners, and researchers can discuss, analyze, criticize, synthesize, communicate, elaborate, and simplify the more-than-promising technology of the semantic Web in the context of information systems. The journal aims to establish value-adding knowledge transfer and personal development channels in three distinctive areas: academia, industry, and government.
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