详细信息

基于信任度匹配的改进PBFT共识算法    

Improved PBFT Consensus Algorithm Based on Trust Matching

文献类型:期刊文献

中文题名:基于信任度匹配的改进PBFT共识算法

英文题名:Improved PBFT Consensus Algorithm Based on Trust Matching

作者:季钰翔[1];黄建华[1];王喆[1];郑红[1];唐瑞琮[2]

机构:[1]华东理工大学信息科学与工程学院,上海200237;[2]香港DAEX区块链有限公司,上海200120

年份:2021

卷号:48

期号:2

起止页码:303

中文期刊名:计算机科学

外文期刊名:Computer Science

收录:CSTPCD;;北大核心:【北大核心2020】;CSCD:【CSCD_E2021_2022】;

基金:国家自然科学基金(61472139)。

语种:中文

中文关键词:区块链;共识算法;拜占庭容错;信任度;邻居匹配;投票计数

外文关键词:Blockchain;Consensus algorithm;Byzantine fault tolerance;Trust;Neighbor matching;Vote counting

摘要:共识算法是去中心化的区块链系统实现数据状态一致的关键。针对传统的实用拜占庭容错(Practical Byzantine Fault Tolerance,PBFT)共识算法在可扩展性和安全性方面存在的不足,提出一种基于信任度的匹配拜占庭共识算法(Trust-based Matching Byzantine Fault Tolerance,TMBFT)。首先,通过基于信任度的邻居匹配模型来选取部分节点进行投票共识,以降低区块链网络的通信量;其次,引入信任度评价机制来监督邻居节点的行为,确保有效检测出拜占庭节点,保证节点投票的安全性;最后,设计投票计数机制保证了共识结果的一致性,并提高了共识效率。与PBFT相比,TMBFT将通信复杂度从O(N^2)降到O(Nlog2N),有效降低了网络中的通信开销。安全性分析表明,信任度评价机制可降低节点作恶的概率,并有效提高系统安全性。实验结果表明,TMBFT较传统拜占庭算法具有更好的性能优势。
Consensus algorithm is the key to realize data consistency in decentralized blockchain systems.Aiming at the scalability and security problems of Practical Byzantine Fault Tolerance(PBFT),a Trust-based Matching Byzantine Fault Tolerance(TMBFT)algorithm is proposed.Firstly,the trust-based neighbor matching model is used to select some nodes for voting consensus,so as to reduce the traffic of the blockchain network.Secondly,a trust evaluation mechanism is introduced to supervise the behavior of neighbor nodes,to ensure the effective detection of Byzantine nodes and the security of node voting.Finally,a vote counting mechanism is designed to ensure the consistency of consensus results and improve the efficiency of consensus.Compared with PBFT,TMBFT reduces the communication complexity from O(N^2)to O(Nlog2N),and effectively reduces the communication overhead in the network.Security analysis shows that the trust evaluation mechanism reduces the probability of malicious voting and improves the system security effectively.Experimental results show that TMBFT has better performance than the traditional Byzantine algorithm.

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