Can Predictive Filters Detect Gradually Ramping False Data Injection Attacks Against PMUs?
Can Predictive Filters Detect Gradually Ramping False Data Injection Attacks Against PMUs?
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DOI：
10.1109/smartgridcomm.2019.8909739
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发表时间：
2019-05
期刊：
影响因子：
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通讯作者：
Zhigang Chu;Andrea Pinceti;R. Biswas;O. Kosut;A. Pal;L. Sankar
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文献类型：
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作者：
Zhigang Chu;Andrea Pinceti;R. Biswas;O. Kosut;A. Pal;L. Sankar
智能设计的虚假数据注入 (FDI) 攻击已被证明能够绕过基于 χ2 测试的不良数据检测器 (BDD)，从而导致电力系统中的物理后果（例如线路过载）。在本文中，使用综合 PMU 测量和智能设计的 FDI 攻击表明，如果攻击突然注入系统，具有足够精度的预测滤波器能够检测到它。然而，攻击者可以逐渐加大攻击力度以避免被发现，但仍然会对系统造成损害。
Intelligently designed false data injection (FDI) attacks have been shown to be able to bypass the χ2-test based bad data detector (BDD), resulting in physical consequences (such as line overloads) in the power system. In this paper, using synthetic PMU measurements and intelligently designed FDI attacks, it is shown that if an attack is suddenly injected into the system, a predictive filter with sufficient accuracy is able to detect it. However, an attacker can gradually increase the magnitude of the attack to avoid detection, and still cause damage to the system.