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Detection of False Data Injection Attacks Using the Autoencoder Approach

22 May 2020 • Wang Chenguang • Tindemans Simon • Pan Kaikai • Palensky Peter

State estimation is of considerable significance for the power system operation and control. However, well-designed false data injection attacks can utilize blind spots in conventional residual-based bad data detection methods to manipulate measurements in a coordinated manner and thus affect the secure operation and economic dispatch of grids... (read more)

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Detection of False Data Injection Attacks Using the Autoencoder Approach

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