有效的数据共识算法集成FL和区块链动态分区协议PBFT.
1School of Computer Science, Huainan Normal University, Huainan, 232038, China. hnsfxy2022@163.com.
Scientific reports
|November 29, 2025
概括
这项研究引入了一个新的框架,将联合学习和区块链集成为安全的物联网 (IoT) 数据共享. 它提高了隐私和效率,解决了物联网环境中的单点故障和通信开销.
科学领域:
- 计算机科学 计算机科学
- 信息安全 信息安全
- 分布式系统 分布式系统
背景情况:
- 物联网 (IoT) 数据共享面临诸如隐私泄露,单点故障和高通讯开销等挑战.
- 现有的联合学习缺乏强大的协作和容错能力,而传统的PBFT算法则在高并发性和通信复杂性方面扎.
- 在快速发展的物联网环境中,急需安全高效的数据传输解决方案.
研究的目的:
- 为物联网环境提出一个多层数据共享框架,将联合学习和区块链技术集成在一起.
- 增强物联网网络中的数据隐私,安全和传输效率.
- 解决现有解决方案在故障耐受性和通信空头方面的局限性.
主要方法:
- 实施了一个框架,将联合学习与区块链技术相结合.
- 使用差异隐私来实现数据隐私和质量证明 (PoQ) 共识来实现容错.
- 引入了一个用于节点监督的声誉机制.
- 开发了一个改进的PBFT共识算法,具有动态区域分区,以实现高效的数据传输.
主要成果:
- 差异隐私降低数据传输精度只有3.5%与高斯噪声.
- PoQ算法显示,对于容错节点的故障率为14.3%.
- 与单层PBFT相比,优化的PBFT减少了44%的通信频率和63%的交易延迟.
- 该框架实现了高效的物联网数据传输与实时安全.
结论:
- 拟议的多层框架有效地解决了物联网数据共享中的安全性和效率问题.
- 联合学习,区块链,差异隐私,PoQ和优化的PBFT的整合为高并发性物联网场景提供了显著的优势.
- 该解决方案满足实时安全需求,并提高物联网网络中的故障耐受性和通信效率.
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