Online Robust PCA for Malicious Attack-Resilient Wide Area Monitoring
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This poster presents a method for detecting and correcting malicious data corruptions in PMU measurements. Detection of malicious injections is formulated as a compressed sensing problem and the actual signals are recovered using an online robust PCA-based algorithm. Different patterns of malicious injection attacks on PMU data are considered and the effect of corruption and reconstruction using the algorithm is analyzed on wide-area mode metering application. The performance of the proposed algorithm has been evaluated with different subspace selection. Data from a 16-machine, 5-area New England-New York system is used along with a recursive modal estimation algorithm to validate the effectiveness of the proposed approach under ambient and transient conditions.
Submitted by Nilanjan Ray C…
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This poster presents a method for detecting and correcting malicious data corruptions in PMU measurements. Detection of malicious injections is formulated as a compressed sensing problem and the actual signals are recovered using an online robust PCA-based algorithm. Different patterns of malicious injection attacks on PMU data are considered and the effect of corruption and reconstruction using the algorithm is analyzed on wide-area mode metering application. The performance of the proposed algorithm has been evaluated with different subspace selection. Data from a 16-machine, 5-area New England-New York system is used along with a recursive modal estimation algorithm to validate the effectiveness of the proposed approach under ambient and transient conditions.