对电网的最佳数据攻击：利用检测和测量干扰
Optimal Data Attacks on Power Grids: Leveraging Detection & Measurement Jamming
摘要：
电网中的仪表测量容易受到对手的操纵，这可能导致状态估计中的错误。本文提出了一个一般的框架，研究攻击状态估计的对手能够注入坏数据的测量，并进一步干扰他们的接收。通过这两种技术，一种新的“可检测的干扰”攻击的设计，改变状态估计，尽管失败的坏数据检测检查。与通常研究的“隐藏”数据攻击相比，这些攻击具有更低的成本和更广泛的可行操作区域。结果表明，整个域的干扰成本可以分为两个区域，不同的图形切割为基础的配方设计的最佳攻击。从这个结果中产生的最重要的见解是，只有当干扰成本小于坏数据注入成本的一半时，干扰测量的对抗能力才会改变最佳的“可检测干扰”攻击设计。提出了一种多项式时间近似的攻击向量构造算法，并通过IEEE测试系统的仿真验证了该算法在攻击设计中的有效性。
英文摘要：
Meter measurements in the power grid are susceptible to manipulation by adversaries, that can lead to errors in state estimation. This paper presents a general framework to study attacks on state estimation by adversaries capable of injecting bad-data into measurements and further, of jamming their reception. Through these two techniques, a novel `detectable jamming' attack is designed that changes the state estimation despite failing bad-data detection checks. Compared to commonly studied `hidden' data attacks, these attacks have lower costs and a wider feasible operating region. It is shown that the entire domain of jamming costs can be divided into two regions, with distinct graph-cut based formulations for the design of the optimal attack. The most significant insight arising from this result is that the adversarial capability to jam measurements changes the optimal 'detectable jamming' attack design only if the jamming cost is less than half the cost of bad-data injection. A polynomial time approximate algorithm for attack vector construction is developed and its efficacy in attack design is demonstrated through simulations on IEEE test systems.
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