Fragmented asynchronous Byzantine fault-tolerant consensus method and device without trusted third party

Abstract

The invention discloses a fragmentation asynchronous Byzantine fault-tolerant consensus method and device without a trusted third party, and the method comprises the steps: carrying out the fragmentation processing of a node, and employing a consensus mode of 1 main chain + N slave chains; maintaining a corresponding slave chain by each fragment, and maintaining a main chain by representative nodes in the fragments; for on-chip transactions, a consensus is achieved only under the corresponding subnet, and then the on-chip transactions are broadcasted to the representative nodes of other fragments by the representative nodes; for the cross-fragment transaction, the representative node is handed over to carry out consensus on the main chain, and fragments related to the transaction all reach the consensus; if the fragments cannot reach the consensus, other fragment states roll back; and the slave chain only records the on-chip transactions passing the consensus and the cross-chip transactions related to the fragment. The device is used for implementing the method. The method has the advantages of being simple in principle, easy to implement, wide in application range, good in expansibility and the like.

Description

technical field [0001] The invention mainly relates to the technical field of Internet security, in particular to a method and device for a fragmented asynchronous Byzantine fault-tolerant consensus that does not require a trusted third party. Background technique [0002] Among the various types of BFT (Byzantine Fault-Tolerant) consensus, the asynchronous Byzantine Fault Tolerant consensus mechanism has the highest robustness, so it is suitable for harsh scenarios such as large node scale and limited network bandwidth. [0003] However, the existing methods still have some shortcomings: [0004] 1. Low scalability: When the number N of nodes participating in the consensus is large, since each node needs to run N ABA instances in parallel, and each ABA instance in Honey Badger BFT has threshold signature-related calculations, the CPU load Growth will significantly reduce consensus efficiency. [0005] 2. Reduced security: The threshold signature module in Honey Badger BFT...

AI Technical Summary

Problems solved by technology

[0004] 1. Low scalability: When the number N of nodes participating in the consensus is large, since each node needs to run N ABA instances in parallel, and each ABA instance in Honey Badger BFT has threshold signature related calculations, the CPU load Growth will make the consensus efficiency significantly lower

[0005] 2. Reduced security: The threshold signature module in Honey Badger BFT introduces a trusted third party to realize the generation and distribution of private key shares, which has certain security risks

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