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Defending false data injection attack on smart grid network using adaptive CUSUM test

机译:使用自适应CUSUM测试防御智能电网上的虚假数据注入攻击

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In modern smart grid networks, the traditional power grid is enabled by the technological advances in sensing, measurement, and control devices with two-way communications between the suppliers and customers. The smart grid integration helps the power grid networks to be smarter, but it also increases the risk of adversaries because of the currently obsoleted cyber-infrastructure. Adversaries can easily paralyzes the power facility by misleading the energy management system with injecting false data. In this paper, we proposes a defense strategy to the malicious data injection attack for smart grid state estimation at the control center. The proposed “adaptive CUSUM algorithm”, is recursive in nature, and each recursion comprises two inter-leaved stages: Stage 1 introduces the linear unknown parameter solver technique, and Stage 2 applies the multi-thread CUSUM algorithm for quickest change detection. The proposed scheme is able to determine the possible existence of adversary at the control center as quickly as possible without violating the given constraints such as a certain level of detection accuracy and false alarm. The performance of the proposed algorithm is evaluated by both mathematic analysis and numerical simulation.
机译:在现代智能电网网络中,传统的电网是通过感测,测量和控制设备的技术进步以及供应商和客户之间的双向通信来实现的。智能电网集成有助于使电网网络更智能,但由于当前废弃的网络基础设施,它还增加了对手的风险。对手通过注入虚假数据误导能源管理系统,很容易使电力设施瘫痪。本文针对控制中心的智能电网状态估计,提出了针对恶意数据注入攻击的防御策略。提出的“自适应CUSUM算法”本质上是递归的,每个递归包括两个相互交错的阶段:第1阶段引入线性未知参数求解器技术,第2阶段将多线程CUSUM算法用于最快的变化检测。所提出的方案能够在不违反给定约束(例如一定水平的检测精度和错误警报)的情况下,尽快确定控制中心中对手的可能存在。通过数学分析和数值模拟对所提算法的性能进行了评估。

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