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Model-Based and Data-Driven Detectors for Time Synchronization Attacks Against PMUs
KTH, School of Electrical Engineering and Computer Science (EECS), Computer Science, Network and Systems Engineering.ORCID iD: 0000-0002-9988-9545
KTH, School of Electrical Engineering and Computer Science (EECS), Computer Science, Network and Systems Engineering.ORCID iD: 0000-0002-4876-0223
2020 (English)In: IEEE Journal on Selected Areas in Communications, ISSN 0733-8716, E-ISSN 1558-0008, Vol. 38, no 1, p. 169-179Article in journal (Refereed) Published
Abstract [en]

Precise time synchronization of Phasor Measurement Units (PMUs) is critical for monitoring and control of smart grids. Thus, time synchronization attacks (TSAs) against PMUs pose a severe threat to smart grid security. In this paper we present an approach for detecting TSAs based on the interaction between the time synchronization system and the power system. We develop a phasor measurement model and use it to derive an accurate closed form expression for the correlation between the frequency adjustments made by the PMU clock and the resulting change in the measured phase angle, without an attack. We then propose one model-based and three data-driven TSA detectors that exploit the change in correlation due to a TSA. Using extensive simulations, we evaluate the proposed detectors under different strategies for implementing TSAs, and show that the proposed detectors are superior to state-of-the-art clock frequency anomaly detection, especially for unstable clocks.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2020. Vol. 38, no 1, p. 169-179
Keywords [en]
Clocks, Phasor measurement units, Synchronization, Detectors, Phase measurement, Frequency measurement, Power system stability, PMU, time synchronization attacks, phasor measurements, security, cyber-physical systems, correlation, clock synchronization, data-driven detection, machine learning
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
URN: urn:nbn:se:kth:diva-268779DOI: 10.1109/JSAC.2019.2952017ISI: 000510714300015Scopus ID: 2-s2.0-85074856246OAI: oai:DiVA.org:kth-268779DiVA, id: diva2:1396021
Note

QC 20200225

Available from: 2020-02-25 Created: 2020-02-25 Last updated: 2020-02-25Bibliographically approved

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Shereen, EzzeldinDán, György

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