智能电网物联网框架用于预测使用联合学习同型加密的能源消耗
Filip Jerkovic1, Nurul I Sarkar1, Jahan Ali1,2
1Department of Computer and Information Sciences, School of Engineering, Computer and Mathematical Sciences, Auckland University of Technology, Auckland 1010, New Zealand.
Sensors (Basel, Switzerland)
|June 27, 2025
概括
本研究介绍了一种安全的智能电网 (SG) 物联网 (IoT) 框架,使用联合学习 (FL) 和同态加密 (HE) 来预测能源消耗,同时保护用户隐私. 这种新的方法确保了智能电网系统中的数据安全.
科学领域:
- 计算机科学 计算机科学
- 电气工程 电气工程
- 网络安全 网络安全
背景情况:
- 智能电网 (SG) 技术需要为联合学习 (FL) 和物联网 (IoT) 应用程序增强数据隐私.
- 现有的框架努力平衡能源消耗预测与强大的用户隐私保护.
研究的目的:
- 提出一个新的SG物联网框架,集成FL,边缘计算和同态加密 (HE) 以安全地预测能源消耗.
- 在智能电网环境中确保端到端机器学习工作负载安全性和用户隐私.
主要方法:
- 开发了一个利用联合学习 (FL) 和边缘计算原则的框架.
- 实现了Cheon-Kim-Kim-Song (CKKS) 完全同型加密 (HE) 在边缘设备之间进行点对点 (P2P) 数据交换.
- 利用P2P网络在边缘设备之间进行安全通信.
主要成果:
- 拟议的框架成功地预测了SG场景中的能源消耗.
- 通过集成的HE和FL方法,证明了有效地保护用户隐私.
- 验证了端到端机器学习工作负载执行的稳定性和安全性.
结论:
- 新的SG物联网框架为安全的能源消耗预测提供了可行的解决方案.
- 结果为研究人员和开发下一代SG物联网系统的工程师提供了宝贵的见解.
- 结合FL,边缘计算和HE对于未来的安全智能电网进步至关重要.
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