Multi-feature weighted PBFT with reputation monopoly prevention

Practical Byzantine Fault Tolerance (PBFT) imposes a high communication overhead and is susceptible to reputation monopolies in scoring-based consensus. Driven by these limitations, this study proposes a Multi-feature Weighting-based PBFT (MF-PBFT) to mitigate reputation monopoly in trusted nodes. The developed approach retains the traditional grouping and scoring mechanisms by introducing attribute prioritization and objective evaluation of candidate nodes. Moreover, to evaluate node capabilities comprehensively, weights are assigned based on the distribution of scores across multiple attributes, including trust, response speed, and communication efficiency. Furthermore, a score-decay function measures and controls the degree of score decentralization among nodes in the consensus process. Finally, a penalty factor deters malicious nodes from participating in the consensus process. Experimental results demonstrate that MF-PBFT enhances consensus efficiency by selecting robust nodes and fostering fair, decentralized node participation in consensus.

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Publication Details

Journal
Digital Communications and Networks
Published
2026-03-01
DOI
https://doi.org/10.1016/j.dcan.2026.03.012
Primary Topic
Distributed systems and fault tolerance
Type
article
Field-Weighted Citation Impact
0.00
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article

Multi-feature weighted PBFT with reputation monopoly prevention

Mun‐Kyu Lee, Zhongxiao Hao, Tao Guo, Qilie Liu et al.
Digital Communications and Networks
Distributed systems and fault tolerance
article

Multi-feature weighted PBFT with reputation monopoly prevention

Mun‐Kyu Lee, Zhongxiao Hao, Tao Guo, Qilie Liu, Fengjun Shang
article en

Abstract

Practical Byzantine Fault Tolerance (PBFT) imposes a high communication overhead and is susceptible to reputation monopolies in scoring-based consensus. Driven by these limitations, this study proposes a Multi-feature Weighting-based PBFT (MF-PBFT) to mitigate reputation monopoly in trusted nodes. The developed approach retains the traditional grouping and scoring mechanisms by introducing attribute prioritization and objective evaluation of candidate nodes. Moreover, to evaluate node capabilities comprehensively, weights are assigned based on the distribution of scores across multiple attributes, including trust, response speed, and communication efficiency. Furthermore, a score-decay function measures and controls the degree of score decentralization among nodes in the consensus process. Finally, a penalty factor deters malicious nodes from participating in the consensus process. Experimental results demonstrate that MF-PBFT enhances consensus efficiency by selecting robust nodes and fostering fair, decentralized node participation in consensus.

Digital Communications and Networks
Chongqing University of Posts and Telecommunications (CN), Hebei University of Engineering (CN), Inha University (KR)
Peace, Justice and strong institutions
Openalex Percentile: Top 1%
Distributed systems and fault tolerance
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