Privacy-Preserving Data Aggregation for Single Point of Failure in Smart Grid

Qingyu Yang, Ding Zhifan
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Abstract

With the increasing popularity of smart grid and fog computing, fog computing-based network privacy is one of the biggest security challenges for data aggregating in smart grid. Many researchers have proposed corresponding solutions. However, in most schemes, a single fog node is responsible for the data aggregation of the smart meter sub-area within its range, which is prone to the risk of single point of failure. To solve the above problems, this paper designed a fog node allocation strategy based on the fog computing smart grid system model containing fog groups. The fog nodes in fog group are allocated by dynamic priority method to reduce the risk of single point failure. Furthermore, a privacy preserving multidimensional data aggregation scheme is proposed, which supports smart meters to report multiple types of data to control center at one time, so as to realize efficient data processing. Security analysis shows that this scheme can better satisfy the security. The performance analysis shows the advantages of this scheme in computation cost.
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智能电网单点故障数据聚合的隐私保护
随着智能电网和雾计算的日益普及,基于雾计算的网络隐私是智能电网数据聚合面临的最大安全挑战之一。许多研究者提出了相应的解决方案。然而,在大多数方案中,单个雾节点负责其范围内智能电表子区域的数据聚合,容易出现单点故障的风险。针对上述问题,本文设计了一种基于包含雾群的雾计算智能电网系统模型的雾节点分配策略。采用动态优先级法对雾组中的雾节点进行分配,降低了单点故障的风险。在此基础上,提出了一种保护隐私的多维数据聚合方案,支持智能电表同时向控制中心上报多种类型的数据,实现高效的数据处理。安全性分析表明,该方案能较好地满足安全性要求。性能分析表明了该方案在计算成本方面的优势。
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