向安全智能电网推进:针对智能欺骗的保护建议

Charith Wickramaarachchi, R. Kannan, C. Chelmis, V. Prasanna
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引用次数: 2

摘要

保护反映输电网物理状态的状态估计的完整性对输电网的安全运行至关重要。现有保护智能电网中关键状态估计免受数据欺骗攻击的方法假设了一组静态的关键总线。相反,我们提出了一种基于奖励收集斯坦纳树公式的广义最优保护方案,该方案捕获了总线的临界性和保护成本。我们认为总线的临界性可以随着时间的推移而变化,并提出了一套针对智能电网中数据欺骗攻击的自适应保护的最佳方案。接下来,我们注意到这种最优方案在计算上是难以处理的,并且提出了具有多项式时间复杂度的启发式方法。我们使用公开可用的传输网络数据集模拟来评估提出的保护方案。仿真结果表明,所提出的启发式算法接近最优结果,同时能够适应大型传输网络。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
PReSS towards a secure smart grid: Protection recommendations against smart spoofing
Protecting the integrity of state estimates that inform the physical state of a power transmission network is vital for the safe operation. Existing methods to protect the critical state estimates in smart-grid against data spoofing attacks assume a static set of critical buses. Instead, we propose a generalized optimal protection scheme based on a prize-collecting Steiner tree formulation that captures the criticality of buses and protection cost. We argue that the criticality of buses can change over time, and present a set of optimal schemes for adaptive protection against data spoofing attacks in smart grids. Next, we note that such optimal schemes are computationally intractable and propose heuristics with polynomial time complexity. We evaluate the proposed protection schemes using simulations on publicly available transmission network datasets. Simulation results show that the proposed heuristics closely approximate the optimal results while being able to scale for large transmission networks.
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