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ARTICLE
CRBFT: A Byzantine Fault-Tolerant Consensus Protocol Based on Collaborative Filtering Recommendation for Blockchains
1 He’nan Province Key Laboratory of Information Security, Information Engineering University, Zhengzhou, 450000, China
2 School of Cyber Science Engineering, Zhengzhou University, Zhengzhou, 450000, China
* Corresponding Author: Xuehui Du. Email:
Computers, Materials & Continua 2024, 80(1), 1491-1519. https://doi.org/10.32604/cmc.2024.052708
Received 11 April 2024; Accepted 06 June 2024; Issue published 18 July 2024
Abstract
Blockchain has been widely used in finance, the Internet of Things (IoT), supply chains, and other scenarios as a revolutionary technology. Consensus protocol plays a vital role in blockchain, which helps all participants to maintain the storage state consistently. However, with the improvement of network environment complexity and system scale, blockchain development is limited by the performance, security, and scalability of the consensus protocol. To address this problem, this paper introduces the collaborative filtering mechanism commonly used in the recommendation system into the Practical Byzantine Fault Tolerance (PBFT) and proposes a Byzantine fault-tolerant (BFT) consensus protocol based on collaborative filtering recommendation (CRBFT). Specifically, an improved collaborative filtering recommendation method is designed to use the similarity between a node’s recommendation opinions and those of the recommender as a basis for determining whether to adopt the recommendation opinions. This can amplify the recommendation voice of good nodes, weaken the impact of cunning malicious nodes on the trust value calculation, and make the calculated results more accurate. In addition, the nodes are given voting power according to their trust value, and a weight random election algorithm is designed and implemented to reduce the risk of attack. The experimental results show that CRBFT can effectively eliminate various malicious nodes and improve the performance of blockchain systems in complex network environments, and the feasibility of CRBFT is also proven by theoretical analysis.Keywords
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