A Survey on the Cyber Attacks Against Non-linear State Estimation in Smart Grids

Wang, Jingxuan; Hui, Lucas Chi Kwong; Yiu, Siu-Ming; Cui, Xingmin; Wang, Eric; Fang, Junbin

doi:10.1007/978-3-319-40253-6_3

Cited by 4 publications

(2 citation statements)

References 30 publications

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“…The physical systems and the information system form the Cyber-Physical Systems (CPS), which have attracted extensive attention recently [9,10]. The coupling process makes it possible to damage the physical systems through cyber systems [11][12][13][14][15][16][17] and makes the physical systems more vulnerable. Currently, it is difficult for both IT people and people from physical systems to understand the risk.…”

Section: Introductionmentioning

confidence: 99%

Robustness of Cyber-Physical Systems against Simultaneous, Sequential and Composite Attack

et al. 2018

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In this paper, a failure model of Cyber-Physical systems and an attack model are proposed. We divide the attacks into three kinds: simultaneous attack, sequential attack and composite attack. Through numerical simulations, we find that: (1) the sequential attack may bring more damage in single physical systems; (2) the coupling process of cyber system and physical systems makes it possible that sequential attack causes more damage than simultaneous attacks when the attackers only attack the cyber system; (3) with some target sets, composite attack leads to more failures than both simultaneous attack and sequential attack. The above results suggest that defenders should take all the three kinds of attacks into account when they select the critical nodes.

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Section: Introductionmentioning

confidence: 99%

Robustness of Cyber-Physical Systems against Simultaneous, Sequential and Composite Attack

et al. 2018

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“…To fight against this attack, existing works focus on the detection of data injection attacks and the protection of nonlinear measurements [4,5]. Detectors utilizing the sparsity and low rank of the system topology are proposed in [6][7][8].…”

Section: Introductionmentioning

confidence: 99%

F-DDIA: A Framework for Detecting Data Injection Attacks in Nonlinear Cyber-Physical Systems

Wang

Hui

Yiu

et al. 2017

Security and Communication Networks

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Data injection attacks in a cyber-physical system aim at manipulating a number of measurements to alter the estimated real-time system states. Many researchers recently focus on how to detect such attacks. However, most of the detection methods do not work well for the nonlinear systems. In this paper, we present a compressive sampling methodology to identify the attack, which allows determining how many and which measurement signals are launched. The sparsity feature is used. Generally, our methodology can be applied to both linear and nonlinear systems. The experimental testing, which includes realistic load patterns from NYISO with various attack scenarios in the IEEE 14-bus system, confirms that our detector performs remarkably well.

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Realizing an Internet of Secure Things: A Survey on Issues and Enabling Technologies

Hamad

Sheng

Zhang

et al. 2020

IEEE Commun. Surv. Tutorials

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A Survey on the Cyber Attacks Against Non-linear State Estimation in Smart Grids

Cited by 4 publications

References 30 publications

Robustness of Cyber-Physical Systems against Simultaneous, Sequential and Composite Attack

Robustness of Cyber-Physical Systems against Simultaneous, Sequential and Composite Attack

F-DDIA: A Framework for Detecting Data Injection Attacks in Nonlinear Cyber-Physical Systems

Realizing an Internet of Secure Things: A Survey on Issues and Enabling Technologies

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