By Peng Cheng, Heng Zhang, Jiming Chen
Cyber protection for commercial keep an eye on platforms: From the point of view of Close-Loop presents a accomplished technical consultant on updated new safe protecting theories and applied sciences, novel layout, and systematic figuring out of safe structure with useful purposes. The ebook contains 10 chapters, that are divided into 3 parts.
The first 3 chapters greatly introduce safe country estimation applied sciences, offering a scientific presentation at the newest development in safety matters concerning country estimation. the subsequent 5 chapters concentrate on the layout of safe suggestions regulate applied sciences in business keep watch over structures, exhibiting a unprecedented distinction from that of conventional safe protecting techniques from the point of view of community and verbal exchange. The final chapters difficult at the systematic safe keep watch over structure and algorithms for numerous concrete software scenarios.
The authors offer distinct descriptions on assault version and process research, intrusion detection, safe kingdom estimation and keep watch over, video game conception in closed-loop structures, and diverse cyber defense purposes. The e-book comes in handy to an individual drawn to safe theories and applied sciences for commercial regulate systems.
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Extra info for Cyber security for industrial control systems : from the viewpoint of close-loop
IEEE, 2010. 31. L. Shi, P. Cheng, and J. Chen. Sensor data scheduling for optimal state estimation with communication energy constraint. Automatica, 47(8):1693– 1698, 2011. 30 Cyber Security for Industrial Control Systems 32. L. Shi, M. Epstein, and R. M. Murray. Kalman filtering over a packetdropping network: a probabilistic perspective. IEEE Transactions on Automatic Control, 55(3):594–604, 2010. 33. L. S. Jia, Y. Mo, and B. Sinopoli. Sensor scheduling over a packetdelaying network. Automatica, 47(5):1089–1092, 2011.
37), we have e(t + 1) = (A + KC)e(t) + (B + KD)w(t), e(0) = 0, r(t) = Ce(t) + Dw(t). 36). 33) with a detectable pair of (A,C) and y(0 : T ) = 0, then x(0 : T ) ∞ ≤ inf K:A+KC strictly stable w(:) E(K) 1 δ ∞ ≤ δ. 8 The assumption that (A,C) is detectable implies the existence of K such that A + KC is strictly stable. 37). The condition y(0 : T ) = 0 implies that x(0 ˆ : T ) = 0. 4 we have x(0 : T ) ∞ = x(0 : T ) − x(0 ˆ : T) = e(0 : T ) ∞ ≤ e(:) ∞ ∞ ≤ E(K) 1 δ. 41). 3 Fundamental Limit This subsection is devoted to establishing a nonexistence proof of a secure estimator under certain conditions.
1 Introduction In this chapter, we consider the problem of inferring the system state from sensory data in an adversarial environment, where some of the sensors are compromised by an adversary and can report arbitrary readings. Our goal is to construct a secure state estimator, whose estimation error is bounded regardless of the adversary’s action. 2, we consider the estimation problem in a static setting, where we try to estimate the state using the measurements collected at a single time step.