Coherency-Based Detection Algorithm for Synchrophasor Cyberattacks
The wide area monitoring system (WAMS) is critical for power system situational awareness, but represents a growing cybersecurity vulnerability. Malicious adversaries may seek to compromise one or more PMUs in order to effect control decisions that unnecessarily disrupt typical grid operations. One...
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| Veröffentlicht in: | 2019 North American Power Symposium (NAPS) S. 1 - 6 |
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01.10.2019
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| Abstract | The wide area monitoring system (WAMS) is critical for power system situational awareness, but represents a growing cybersecurity vulnerability. Malicious adversaries may seek to compromise one or more PMUs in order to effect control decisions that unnecessarily disrupt typical grid operations. One example of a particularly pernicious attack vector is the spoofing or replaying of a fault event using one or more compromised PMUs. This work documents the development and validation of a coherency-based cyberattack detection algorithm that integrates a sliding-window singular value decomposition (SVD) with physics-based partitioning analysis to achieve accurate classification of events. Special consideration is given to discerning a sophisticated fault-replay or fault spoofing attack from actual faults. A software-based cybersecurity testbed has been developed for rigorous testing of the algorithm. The algorithm is further validated using simulated synchrophasor datasets obtained from a MinniWECC 63-bus test system. Results show that the algorithm can successfully detect fault-replay attacks even when over half of the PMUs are compromised. |
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| AbstractList | The wide area monitoring system (WAMS) is critical for power system situational awareness, but represents a growing cybersecurity vulnerability. Malicious adversaries may seek to compromise one or more PMUs in order to effect control decisions that unnecessarily disrupt typical grid operations. One example of a particularly pernicious attack vector is the spoofing or replaying of a fault event using one or more compromised PMUs. This work documents the development and validation of a coherency-based cyberattack detection algorithm that integrates a sliding-window singular value decomposition (SVD) with physics-based partitioning analysis to achieve accurate classification of events. Special consideration is given to discerning a sophisticated fault-replay or fault spoofing attack from actual faults. A software-based cybersecurity testbed has been developed for rigorous testing of the algorithm. The algorithm is further validated using simulated synchrophasor datasets obtained from a MinniWECC 63-bus test system. Results show that the algorithm can successfully detect fault-replay attacks even when over half of the PMUs are compromised. |
| Author | Wang, Honggang Hart, Philip Acharya, Sowmya |
| Author_xml | – sequence: 1 givenname: Philip surname: Hart fullname: Hart, Philip organization: GE Global Research,Niskayuna,New York,USA – sequence: 2 givenname: Sowmya surname: Acharya fullname: Acharya, Sowmya organization: GE Global Research,Niskayuna,New York,USA – sequence: 3 givenname: Honggang surname: Wang fullname: Wang, Honggang organization: GE Global Research,Niskayuna,New York,USA |
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| Snippet | The wide area monitoring system (WAMS) is critical for power system situational awareness, but represents a growing cybersecurity vulnerability. Malicious... |
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| SubjectTerms | Circuit faults coherency Computer crime Cyberattack detection algorithm Detection algorithms event classification fault Mathematical model Partitioning algorithms Phasor measurement units Power systems replay attack synchrophasors WAMS |
| Title | Coherency-Based Detection Algorithm for Synchrophasor Cyberattacks |
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