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Algorithmic Approaches to Characterizing Power Flow Cyber-Attack Vulnerabilities

机译:表征潮流网络攻击漏洞的算法方法

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As power grid control systems become increasingly automated and distributed, security has become a significant design concern. Systems increasingly expose new avenues, at a variety of levels, for attackers to exploit and enable widespread disruptions and/or surveillance. Much prior work has explored the implications of attack models focused on false data injection at the front-end of the control system (i.e. during state estimation) [1]. Instead, in this paper we focus on characterizing the inherent cyber-attack vulnerabilities with power flow. Power flow (and power flow constraints) are at the core of many applications critical to operation of power grids (e.g. state estimation, economic dispatch, contingency analysis, etc.). We propose two algorithmic approaches for characterizing the vulnerability of buses within power grids to cyber-attacks. Specifically, we focus on measuring the instability of power flow to attacks which manifest as either voltage or power related errors. Our results show that attacks manifesting as voltage errors are an order of magnitude more likely to cause instability than attacks manifesting as power related errors (and 5x more likely for state estimation as compared to power flow).
机译:随着电网控制系统变得越来越自动化和分布式,安全性已成为重要的设计关注点。系统越来越多地在各个层次上提供新的途径,供攻击者利用并实现广泛的破坏和/或监视。许多先前的工作已经探索了针对控制系统前端(即,在状态估计期间)错误数据注入的攻击模型的含义[1]。取而代之的是,在本文中,我们着重描述具有潮流的固有网络攻击漏洞。潮流(和潮流约束)是许多对电网运行至关重要的应用程序的核心(例如状态估计,经济调度,应急分析等)。我们提出了两种算法方法来表征电网中的总线对网络攻击的脆弱性。具体来说,我们专注于衡量攻击的功率流的不稳定性,这些攻击表现为与电压或功率相关的错误。我们的结果表明,表现为电压误差的攻击比表现为与功率相关的误差的攻击更容易造成不稳定性(与功率流相比,状态估计的可能性要高5倍)。

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