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A Semidefinite Programming Relaxation under False Data Injection Attacks against Power Grid AC State Estimation
Univ Calif Berkeley, Dept Elect Engn & Comp Sci, Berkeley, CA 94720 USA..
Univ Calif Berkeley, Dept Ind Engn & Operat Res, Berkeley, CA 94720 USA..
KTH, School of Electrical Engineering and Computer Science (EECS), Automatic Control.ORCID iD: 0000-0001-9940-5929
2017 (English)In: 55th Annual Allerton Conference on Communication, Control, and Computing, Allerton 2017, Institute of Electrical and Electronics Engineers (IEEE), 2017, p. 236-243Conference paper, Published paper (Refereed)
Abstract [en]

The integration of sensing and information technology renders the power grid susceptible to cyber-attacks. To understand how vulnerable the state estimator is, we study its behavior under the worst attacks possible. A general false data injection attack (FDIA) based on the AC model is formulated, where the attacker manipulates sensor measurements to mislead the system operator to make decisions based on a falsified state. To stage such an attack, the optimization problem incorporates constraints of limited resources (allowing only a limited number of measurements to be altered), and stealth operation (ensuring the cyber hack cannot be identified by the bad data detection algorithm). Due to the nonlinear AC power flow model and combinatorial selection of compromised sensors, the problem is nonconvex and cannot be solved in polynomial time; however, it is shown that convexification of the original problem based on a semidefinite programming (SDP) relaxation and a sparsity penalty is able to recover a near-optimal solution. This represents the first study to solve the AC-based FDIA. Simulations on a 30-bus system illustrate that the proposed attack requires only sparse sensor manipulation and remains stealthy from the residual-based bad data detection mechanism. In light of the analysis, this study raises new challenges on grid defense mechanism and attack detection strategy.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2017. p. 236-243
Series
Annual Allerton Conference on Communication Control and Computing, ISSN 2474-0195
National Category
Computer Sciences
Identifiers
URN: urn:nbn:se:kth:diva-226277DOI: 10.1109/ALLERTON.2017.8262743ISI: 000428047800033Scopus ID: 2-s2.0-85048023842ISBN: 978-1-5386-3266-6 OAI: oai:DiVA.org:kth-226277DiVA, id: diva2:1198952
Conference
55th Annual Allerton Conference on Communication, Control, and Computing, Allerton 2017, Allerton House Monticello, United States, 3 October 2017 through 6 October 2017 55th Annual Allerton Conference on Communication, Control, and Computing, Allerton 2017, Allerton House Monticello, United States, 3 October 2017 through 6 October 2017
Note

QC 20180419

Available from: 2018-04-19 Created: 2018-04-19 Last updated: 2018-06-11Bibliographically approved

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Johansson, Karl H.

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