摘要
针对联盟链微电网电力交易场景的高吞吐量、高数据安全性及数据透明性的需求,提出一种在贡献值模型下的基于可验证随机函数(Verifiable Random Function,VRF)与基于BLS(Boneh-Lynn-Shacham Threshold Signatures,BLS)门限签名的改进实用拜占庭容错共识算法(Contribution Value Model,Verifiable Random Function and Boneh-Lynn-Shacham Threshold Signatures Practical ByzantineFault Tolerance,CVB-PBFT)。CVB-PBFT算法通过贡献值模型筛选高贡献节点参与共识,采用VRF和安全随机函数选举不可预测的主节点,结合节点轮换和检测机制以及BLS签名优化通信流程,显著提高算法的性能和安全性。经实验证明,该算法能够有效防御恶意攻击,降低通信开销,并提升共识效率,满足微电网电力交易对时效性和安全性的要求。
In order to address the needs for high throughput,high data security,and data transparency in the context of alliance chain microgrid transactions,this paper proposes an improved Practical Byzantine Fault Tolerance(PBFT)consensus algorithm under a contribution value model,integrating Verifiable Random Function(VRF)and Boneh-Lynn-Shacham Threshold Signatures(BLS),termed CVB-PBFT.The CVB-PBFT algorithm filters high-contribution nodes for consensus participation using a contribution value model,selects an unpredictable primary node via VRF and secure random function,and significantly enhances performance and security by combining node rotation and detection mechanisms with BLS signature-optimized communication processes.Experimental results demonstrate that this algorithm effectively defends against malicious attacks,reduces communication overhead,and enhances consensus efficiency,meeting the requirements for timeliness and security in microgrid power trading.
作者
张月圆
张春远
王永利
高卓逸
武子豪
ZHANG Yueyuan;ZHANG Chunyuan;WANG Yongli;GAO Zhuoyi;WU Zihao(Inner Mongolia Power(Group)Co.,Ltd.,Hohhot 010010,China;Inner Mongolia Autonomous Region Private Economy Development Promotion Center,Hohhot 010090,China;Inner Mongolia Power(Group)Co.,Ltd.,Ordos Power Supply Branch,Ordos 017004,China;School of Control and Computer Engineering,North China Electric Power University,Baoding 071003,China)
出处
《内蒙古电力技术》
2024年第5期52-61,共10页
Inner Mongolia Electric Power
基金
内蒙古电力(集团)有限责任公司科技项目“基于互信理论的能源联盟链认证体系关键技术研究”(LX2023-5-11)。
关键词
微电网
实用拜占庭容错
可验证随机函数
贡献值模型
门限签名
microgrid
Practical Byzantine Fault Tolerance(PBFT)
Verifiable Random Function(VRF)
contribution value model
threshold signatures
