2015 23rd European Signal Processing Conference (EUSIPCO) 2015
DOI: 10.1109/eusipco.2015.7362787
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Sensitivity analysis of the sequential test for detecting cyber-physical attacks

Abstract: This paper deals with the problem of detecting cyberphysical attacks on Supervisory Control And Data Acquisition (SCADA) systems. The discrete-time state space model is used to describe the systems. The attacks are modeled as additive signals of short duration on both state evolution and sensor measurement equations. The steady-state Kalman filter is employed to generate the sequence of innovations. Next, these independent random variables are used as entries of the Variable Threshold Window Limited CUmulative… Show more

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Cited by 5 publications
(3 citation statements)
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“…We assume that observations { X n ; n = 1, 2, ...} are independent and identically distributed with prechange N 0 σ 2 and postchange N θ σ 2 distributions, respectively, so that L X n = exp θ σ 2 X n θ 2 2 σ 2 and F ∞ in Equation 4 is the LogNormal CDF with parameters θ 2 2 σ 2 θ 2 σ 2 . Notice that the Gaussian assumption is rather standard model for plants and CPS. This is not only due to its mathematical tractability, but is also motivated by the fact that the processes under surveillance are often physical variables subject to measurement noise (for which the Gaussian is the leading model) or are anyway the result of several independent contributions so again the central limit theorem suggests, in absence of more reliable models or contradicting evidence, the Gaussian assumption.…”
Section: Simulation Resultsmentioning
confidence: 99%
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“…We assume that observations { X n ; n = 1, 2, ...} are independent and identically distributed with prechange N 0 σ 2 and postchange N θ σ 2 distributions, respectively, so that L X n = exp θ σ 2 X n θ 2 2 σ 2 and F ∞ in Equation 4 is the LogNormal CDF with parameters θ 2 2 σ 2 θ 2 σ 2 . Notice that the Gaussian assumption is rather standard model for plants and CPS. This is not only due to its mathematical tractability, but is also motivated by the fact that the processes under surveillance are often physical variables subject to measurement noise (for which the Gaussian is the leading model) or are anyway the result of several independent contributions so again the central limit theorem suggests, in absence of more reliable models or contradicting evidence, the Gaussian assumption.…”
Section: Simulation Resultsmentioning
confidence: 99%
“…The CUSUM has been largely used for monitoring and quickly detecting changes in industrial plants, and more recently for securing CPS. In the latter case, examples of monitored variables are power flows in smart grids, or pressure in water treatment plants . Such signals can be deceived by different types of attacks, thus affecting in turn the correct functioning of the system .…”
Section: Quickest Change‐detection Approachesmentioning
confidence: 99%
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