<b>Hyperledger Fabric</b>共识机制优化方案

孟吴同; 张大伟

doi:10.16383/j.aas.c190516

Hyperledger Fabric共识机制优化方案

doi: 10.16383/j.aas.c190516

孟吴同^{1, 2,},
张大伟^{1, 2,}

1.
智能交通数据安全与隐私保护技术北京市重点实验室北京 100044
2.
北京交通大学计算机与信息技术学院北京 100044

基金项目: 国家留学基金(201807095023)资助

详细信息

作者简介:
孟吴同：北京交通大学硕士研究生. 2017年获得河北大学网络工程学士学位. 主要研究方向为区块链.E-mail: mengwt@bjtu.edu.cn

张大伟：北京交通大学计算机与信息技术学院副教授. 2004年获得北京航空航天大学通信与信息系统专业博士学位. 主要研究方向为区块链, 安全协议, 可信计算. 本文通信作者.E-mail: dwzhang@bjtu.edu.cn

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出版历程
- 收稿日期: 2019-07-07
- 录用日期: 2019-12-15
- 网络出版日期: 2020-01-20
- 刊出日期: 2021-08-20

Optimization Scheme for Hyperledger Fabric Consensus Mechanism

MENG Wu-Tong^{1, 2
,},
ZHANG Da-Wei^{1, 2
,}

1.
Beijing Key Laboratory of Security and Privacy in Intelligent Transportation, Beijing 100044
2.
School of Computer and Information Technology, Beijing Jiaotong University, Beijing 100044

Funds: Supported by China Scholarship Council (201807095023)

More Information

Author Bio:
MENG Wu-Tong　Master student at the School of Computer and Information Technology, Beijing Jiaotong University. He received his bachelor degree in network engineering from Hebei University in 2017. His main research interest is blockchain

ZHANG Da-Wei　Associate professor at the School of Computer and Information Technology, Beijing Jiaotong University. He received his Ph. D. degree in communication and information system from Beihang University in 2004. His research interest covers blockchain, security protocol and trusted computing. Corresponding author of this paper

摘要

摘要:
针对Hyperledger Fabric使用固定背书节点处理交易所带来的安全风险和性能瓶颈问题, 提出了一种非交互、可验证的随机化背书节点优化方案. 基于“背书−排序−验证”的Hyperledger fabric共识模型, 引入背书节点候选集, 使用可验证随机函数随机抽取背书节点进行交易背书, 实现了背书节点的非交互式可验证随机选取和背书过程的并行处理. 分析和实验表明, 优化后的共识机制具有更高的安全性和更快的交易处理速度.
- 区块链 /
- 共识机制 /
- 可验证随机函数 /
- Hyperledger fabric
Abstract:
To solve the problem of the security risk and processing bottleneck caused by handling all transactions with a fixed endorsement node in hyperledger fabric, a non-interactive and verifiable randomized endorsement scheme is proposed. On the basis of the “endorse-sort-verify” consensus mechanism, the non-interactive and verifiable random selection of the endorsement node and the parallel endorsement process are implemented by introducing the endorsement node candidate set and using the verifiable random function to randomly extract the endorsement node to endorse each transaction. Analysis and experiments show that the optimized consensus mechanism has higher security and faster transaction processing speed.
- Blockchain /
- consensus mechanism /
- verifiable random function /
- hyperledger fabric

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图 1 Hyperledger fabric共识机制

Fig. 1 Hyperledger fabric consensus mechanism

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图 2 优化后的Hyperledger fabric共识机制

Fig. 2 Optimized hyperledger fabric consensus mechanism

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图 3 敌手攻击成功的概率

Fig. 3 Probability of successful enemy attack

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图 4 实验网络拓扑图

Fig. 4 Network topology of experiment

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图 5 原有方案与优化方案交易时间对比

Fig. 5 The comparison of transaction time between original scheme and optimized scheme

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图 6 原有方案与优化方案交易延迟对比

Fig. 6 The comparison of transaction delay between original scheme and optimized scheme

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图 7 原有方案与优化方案通信成本对比

Fig. 7 The comparison of communication cost between original scheme and optimization scheme

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表 1 优化方案与其他共识机制的对比

Table 1 Comparison of optimization scheme with other consensus mechanisms

共识机制	VRF 的作用	共识原理	资源消耗	容错能力
Algorand	出块节点的选取	VRF + PBFT	低	$3f+1$
Definity	出块节点的选取	VRF + PoS	较高	$2f+1$
Ouroboros Praos	出块节点的选取	VRF + PoS	较高	$2f+1$
优化方案	背书节点的选取	VRF + 背书 + 排序 + 验证	低	F($m,t$)

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表 2 敌手攻击成功次数

Table 2 Number of successful attacks by adversary

	交易次数	敌手成功次数	攻击成功概率
原始方案	1 000	1 000	100 %
优化方案	100 000	686	6.86 %

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表 3 无背书节点情况发生次数

Table 3 Frequency of nonoccurence of endorsing peer

交易次数	是否使用计时重传	无背书节点情况发生次数
1 000	否	2
100 000	否	17
1 000	是	0
100 000	是	0

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表 4 可验证随机函数各部分算法运行时间

Table 4 Running time of each part of the VRF algorithm

算法	次数	总时间 (ms)	平均时间 (ms)
生成密钥	10000	2878.3546	0.2878
生成随机数和证明	10000	10395.3927	1.0395
验证随机数和证明	10000	12874.6190	1.2875

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