Online Identification and Data Recovery for PMU Data Manipulation Attack
Online Identification and Data Recovery for PMU Data Manipulation Attack
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DOI：
10.1109/tsg.2019.2892423
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发表时间：
2019-11-01
影响因子：
9.6
通讯作者：
Wang, Zhiwei
中科院分区：
文献类型：
--
作者：
Wang, Xinan;Shi, Di;Wang, Zhiwei
一些现代智能电网基础设施，例如相量测量单元（PMU），由于其对信息和通信技术的依赖性越来越大，因此容易受到网络攻击。通常，针对网络攻击的现有解决方案集中于创建冗余和/或增强传感和通信网络的安全级别。这些解决方案需要大量的离线工作，因此在经济上是昂贵的。此外，它们在处理动态攻击时通常效率低下。提出了一种新的基于密度的空间聚类方法，用于PMU测量数据操纵攻击的在线检测、分类和数据恢复。所提出的方法是纯粹的数据驱动，适用于同时多测量攻击，而不需要在现有的基础设施中的额外硬件。所提出的方法也是独立于传统的状态估计。综合的案例研究证明了所提出的方法的有效性。
Some of the modern smart grid infrastructures, phasor measurement units (PMUs) for instance, are vulnerable to cyberattacks due to their ever-increasing dependence on information and communications technologies. In general, existing solutions to cyberattacks focus on creating redundancy and/or enhancing security levels of sensing and communication networks. These solutions require intensive offline efforts and therefore are economically expensive. Further, they are generally inefficient when dealing with dynamic attacks. This paper proposes a novel density-based spatial clustering approach for online detection, classification, and data recovery for data manipulation attacks to PMU measurements. The proposed method is purely data-driven and is applicable to simultaneous multi-measurement attacks without requiring additional hardware in the existing infrastructure. The proposed approach is also independent of the conventional state estimation. Comprehensive case studies demonstrate the effectiveness of the proposed method.