Computer Science

Computer Science ›› 2021, Vol. 48 ›› Issue (2): 303-310.doi: 10.11896/jsjkx.200500112

• Information Security • Previous Articles     Next Articles

Improved PBFT Consensus Algorithm Based on Trust Matching

JI Yu-xiang1, HUANG Jian-hua1, WANG Zhe1, ZHENG Hong1, TANG Rui-cong2   

  1. 1 School of Information Science & Engineering,East China University of Science & Technology,Shanghai 200237,China
    2 Hong Kong DAEX Blockchain Limited,Shanghai 200120,China
  • Received:2020-05-22 Revised:2020-10-05 Online:2021-02-15 Published:2021-02-04
  • About author:JI Yu-xiang,born in 1996,postgra-duate.His main research interests include blockchain and so on.
    HUANG Jian-hua,born in 1963,Ph.D,professor,is a member of China Computer Federation.His main research interests include computer network,information security and blockchain.
  • Supported by:
    The National Natural Science Foundation of China(61472139).

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Abstract: 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(N2) 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.

Key words: Blockchain, Byzantine fault tolerance, Consensus algorithm, Neighbor matching, Trust, Vote counting

CLC Number: 

  • TP393
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