On malicious data attacks on power system state estimation

Oliver Kosut, Liyan Jia, Robert J. Thomas, Lang Tong

Research output: Chapter in Book/Report/Conference proceedingConference contribution

64 Scopus citations

Abstract

The problem of detecting and characterizing impacts of malicious attacks against smart grid state estimation is considered. Different from the classical bad data detection for state estimation, the detection of malicious data injected by an adversary must take into account carefully designed attacks capable of evading conventional bad data detection. A Bayesian framework is presented for the characterization of fundamental tradeoffs at the control center and for the adversary. For the control center, a detector based on the generalized likelihood ratio test (GRLT) is introduced and compared with conventional bad detection detection schemes. For the adversary, the tradeoff between increasing the mean square error (MSE) of the state estimation vs. the probability of being detected by the control center is characterized. A heuristic is presented for the design of worst attack.

Original languageEnglish (US)
Title of host publication2010 45th International Universities' Power Engineering Conference, UPEC 2010
StatePublished - Dec 1 2010
Externally publishedYes
Event2010 45th International Universities' Power Engineering Conference, UPEC 2010 - Cardiff, United Kingdom
Duration: Aug 31 2010Sep 3 2010

Publication series

NameProceedings of the Universities Power Engineering Conference

Other

Other2010 45th International Universities' Power Engineering Conference, UPEC 2010
CountryUnited Kingdom
CityCardiff
Period8/31/109/3/10

Keywords

  • Energy management systems
  • False data attack
  • Smart grid security
  • State estimation

ASJC Scopus subject areas

  • Energy Engineering and Power Technology

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