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Consortium Chain Consensus Vulnerability and Chain Generation Mechanism.

Authors :
Rui Qiao
Shi Dong
Source :
Computers, Materials & Continua; 2023, Vol. 77 Issue 2, p2505-2527, 23p
Publication Year :
2023

Abstract

Effectively identifying and preventing the threat of Byzantine nodes to the security of distributed systems is a challenge in applying consortium chains. Therefore, this paper proposes a new consortium chain generation model, deeply analyzes the vulnerability of the consortium chain consensus based on the behavior of the nodes, and points out the effects of Byzantine node proportion and node state verification on the consensus process and system security. Furthermore, the normalized verification node aggregation index that represents the consensus ability of the consortium organization and the trust evaluation function of the verification node set is derived. When either of the two is lower than the threshold, the consortium institution or the verification node set members are dynamically adjusted. On this basis, an innovative consortium chain generation mechanism based on the Asynchronous Binary Byzantine Consensus Mechanism (ABBCM) is proposed. Based on the extended consortium chain consensus mechanism, a certain consensus value set can be combined into multiple proposals, which can realize crossdomain asynchronous message passing between multi-consortium chains without reducing the system's security. In addition, experiments are carried out under four classical Byzantine Attack (BA) behaviors, BA1 to BA4. The results show that the proposed method can obtain better delay than the classical random Byzantine consensus algorithm Coin, effectively improving the consensus efficiency based on asynchronous message passing in the consortium chain and thus meeting the throughput of most Internet of Things (IoT) applications. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
15462218
Volume :
77
Issue :
2
Database :
Complementary Index
Journal :
Computers, Materials & Continua
Publication Type :
Academic Journal
Accession number :
174091908
Full Text :
https://doi.org/10.32604/cmc.2023.043476