The potential for malicious control in a competitive power systems environment

DeMarco, Christopher L.; Sariashkar, J.V.; Alvarado, F.L.

doi:10.1109/cca.1996.558870

Cited by 24 publications

(31 citation statements)

References 4 publications

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“…Possible genuine failures include variations in demand and supply of power or water, line outages or pipe leakages, and failures of sensors and actuators. Possible cyber-physical attacks include measurements corruption [9], [10], [22] and attacks on the control architecture or the physical state [1], [15], [18], [19].…”

Section: Model Of Monitorsmentioning

confidence: 99%

“…The control centers implement the distributed attack detection procedure described in (15), with G = AC T . It can be verified that the pair (E, A D + GC) is Hurwitz stable, and that ρ (j ωE − A D − GC) −1 A C ) < 1 for all ω ∈ R. As predicted by Theorem 4.3, our distributed attack detection filter is convergent; see Fig.…”

Section: Illustrative Examplesmentioning

confidence: 99%

“…Finally, security issues of specific cyber-physical systems have received considerable attention, such as power networks [15]- [19], linear networks with misbehaving components [20], [21], and water networks [22], [23].…”

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confidence: 99%

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Attack Detection and Identification in Cyber-Physical Systems

Pasqualetti

Dörfler

Bullo

2013

IEEE Trans. Automat. Contr.

1,862

1,166

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Cyber-physical systems are ubiquitous in power systems, transportation networks, industrial process control and critical infrastructures. These systems need to operate reliably in the face of unforeseen failures and external malicious attacks. In this paper (i) we propose a mathematical framework for cyberphysical systems, attacks, and monitors; (ii) we characterize fundamental monitoring limitations from system-theoretic and graph-theoretic perspectives; and (iii) we design centralized and distributed attack detection and identification monitors. Finally, we validate our findings through compelling examples.

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Section: Model Of Monitorsmentioning

confidence: 99%

Section: Illustrative Examplesmentioning

confidence: 99%

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Attack Detection and Identification in Cyber-Physical Systems

Pasqualetti

Dörfler

Bullo

2013

IEEE Trans. Automat. Contr.

1,862

1,166

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“…Specifically, a parameterized decoupling structure allows a covert agent to alter the behavior of the physical plant while remaining undetected from the original controller. Finally, security issues of specific systems have received considerable attention, such as power networks [13]- [17], linear networks with misbehaving components [18], [19], and water networks [20], [21]. Contributions.…”

Section: Introductionmentioning

confidence: 99%

“…Fifth, inspired by [13], we consider a competitive power generation scenario (Section V). We exploit our previous findings to characterize all control strategies for a coalition of generators to destabilize other machines involved in the power generation.…”

Section: Introductionmentioning

confidence: 99%

Cyber-physical security via geometric control: Distributed monitoring and malicious attacks

Pasqualetti

Dörfler

Bullo

2012

2012 IEEE 51st IEEE Conference on Decision and Control (CDC)

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Abstract-Cyber-physical systems are ubiquitous in power systems, transportation networks, industrial processes, and critical infrastructures. These systems need to operate reliably in the face of unforeseen failures and external malicious attacks. This paper summarizes and extends our results on the security of cyber-physical systems based on geometric control theory: (i) we propose a mathematical framework for cyberphysical systems, attacks, and monitors; (ii) we characterize fundamental monitoring limitations from system-theoretic and graph-theoretic perspectives; and (iii) we design centralized and distributed attack detection and identification monitors. Finally, we design an attack strategy for a group of power generators to physically compromise the functionality of other generators. Novel contributions include a more general framework, the design of novel centralized and distributed identification monitors, and the attack design case study.

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Control‐channel interactions in diffusive dynamical networks: A graph‐theoretic perspective

Koorehdavoudi

Roy

Torres

et al. 2020

Intl J Robust & Nonlinear

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Control-channel interactions in a linear diffusive network model are studied, with the aim of determining the role of the network's topology in such interactions. Specifically, the influence of a built controller on the infinite and finite zero structure of a second control channel is characterized. The analysis shows how the network's graph topology, the relative positions of the two channels, and the architecture of the built controller influence the zero structure of the second control channel. Further, the influence of low or high gain controller designs on remote channels is examined. The analyses demonstrate that some control architectures and positions can introduce undesirable nonminimum-phase dynamics at remote locations, while others are guaranteed to maintain or promote minimum-phase dynamics.

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The potential for malicious control in a competitive power systems environment

Cited by 24 publications

References 4 publications

Attack Detection and Identification in Cyber-Physical Systems

Attack Detection and Identification in Cyber-Physical Systems

Cyber-physical security via geometric control: Distributed monitoring and malicious attacks

Control‐channel interactions in diffusive dynamical networks: A graph‐theoretic perspective

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