Doctor of Philosophy (PhD)


Electrical and Computer Engineering

Document Type



The use of information technology in electric power grid introduces the vulnerability problem looming the future smart grid. The supervisory control and data acquisition (SCADA)is the first defense, which itself is undermined by potential malicious attacks. This dissertation studies two particular security threats facing the smart grid and SCADA systems: the unobservable attack and the replay attack. The former is well known in fault detection of the power grid and has received renewed interest in the past a few years, while the latter is motivated by the Stuxnet worm allegedly used against the nuclear facilities in Iran. For unobservable attacks, this dissertation adopts the dynamic state estimation approach and treats each bus of the power grid as a dynamic agent. A consensus estimation strategy is proposed to estimate the dynamic states of the power grid, based on which unobservable attacks can be effectively detected. Detection of replay attacks is harder. Two different approaches are proposed in this dissertation. The first is the whitening filter approach that converts the detection of the replay attack into an equivalent white noise detection through whitening a feedback signal. However this approach is less effective, if the replay attack does not change much the whiteness of the filtered feedback signal. Hence a second approach termed as spectrum estimation is proposed. It is shown that the spectrum of the feedback signal in presence of the replay attack can be very different from the case when the replay attack is absent. This approach improves the detection results of the former one. Both are illustrated and examined by the simulation studies.



Document Availability at the Time of Submission

Release the entire work immediately for access worldwide.

Committee Chair

Gu, Guoxiang