Cyber-Physical Attack-Resilient Wide-Area Monitoring, Protection, and Control for the Power Grid

Ashok, Aditya; Manimaran, G.; Wang, Jianhui

doi:10.1109/jproc.2017.2686394

Cited by 218 publications

(90 citation statements)

References 45 publications

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“…With the development of technologies, the traditional power system is undergoing a comprehensive transformation to a smarter, computer-and communication-based grids. Cyber security issues are increasingly closely related to all aspects of the electric grids in generation, transmission, distribution and the end-users [23][24][25][26][27][28]. Many interesting issues have been addressed on the AC power system, but few studies have focused on the DC grids.…”

Section: Literature Surveymentioning

confidence: 99%

Impact of Cyber Attacks on High Voltage DC Transmission Damping Control

et al. 2018

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Hybrid AC/HVDC (AC-HVDC) grids have evolved to become huge cyber-physical systems that are vulnerable to cyber attacks because of the wide attack surface and increasing dependence on intelligent electronic devices, computing resources and communication networks. This paper, for the first time, studies the impact of cyber attacks on HVDC transmission oscillation damping control.Three kinds of cyber attack models are considered: timing attack, replay attack and false data injection attack. Followed by a brief introduction of the HVDC model and conventional oscillation damping control method, the design of three attack models is described in the paper. These attacks are tested on a modified IEEE New England 39-Bus AC-HVDC system. Simulation results have shown that all three kinds of attacks are capable of driving the AC-HVDC system into large oscillations or even unstable conditions.

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Section: Literature Surveymentioning

confidence: 99%

Impact of Cyber Attacks on High Voltage DC Transmission Damping Control

et al. 2018

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“…Second, extensive information on the system model might be exposed to the adversary. There are two ways by which a malicious adversary can obtain information about the power system model: 1) The detailed physical model may be directly leaked to the attacker via disgruntled employees or malicious insiders [10]; 2) The statistical model of the power system can be learned using mathematical tools based on the leaked system operating data. The attackers in the former case can bypass the SE-based detection algorithm by conducting "unobservable attacks" described in [11] or by conducting the packet-reordering integrity attack reported in [12], whereas the adversaries in the latter case can tamper with the measurements without triggering the alarm defined in [9] by replacing the actual measurement sequence with a different sequence that still conforms to the learned statistical model [13].…”

Section: Introductionmentioning

confidence: 99%

An Online Detection Framework for Cyber Attacks on Automatic Generation Control

Huang

Satchidanandan

Kumar

et al. 2018

IEEE Trans. Power Syst.

124

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We propose an online framework to detect cyber attacks on Automatic Generation Control (AGC). A cyber attack detection algorithm is designed based on the approach of Dynamic Watermarking. The detection algorithm provides a theoretical guarantee of detection of cyber attacks launched by sophisticated attackers possessing extensive knowledge of the physical and statistical models of targeted power systems. The proposed framework is practically implementable, as it needs no hardware update on generation units. The efficacy of the proposed framework is validated in both four-area system and 140-bus system. His research interests include modeling and control of large-scale complex systems, smart grids application with renewable energy resources, and electricity markets.

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“…II. RELATED WORK Vulnerability of power grids to failures and attacks has been widely studied [10], [11], [12], [13], [14], [15], [16], [17], [18], [19]. In particular false data injection attacks on power grids and anomaly detection have been studied using the DC power flows in [20], [21], [22], [23], [24], [25].…”

Section: Introductionmentioning

confidence: 99%

EXPOSE the Line Failures Following a Cyber-Physical Attack on the Power Grid

Soltan

Zussman

2019

IEEE Trans. Control Netw. Syst.

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Recent attacks on power grids demonstrated the vulnerability of the grids to cyber and physical attacks. To analyze this vulnerability, we study cyber-physical attacks that affect both the power grid physical infrastructure and its underlying Supervisory Control And Data Acquisition (SCADA) system. We assume that an adversary attacks an area by: (i) disconnecting some lines within that area, and (ii) obstructing the information (e.g., status of the lines and voltage measurements) from within the area to reach the control center. We leverage the algebraic properties of the AC power flows to introduce the efficient EXPOSE Algorithm for detecting line failures and recovering voltages inside that attacked area after such an attack. The EXPOSE Algorithm outperforms the state-of-the-art algorithm for detecting line failures using partial information under the AC power flow model in terms of scalability and accuracy. The main advantages of the EXPOSE Algorithm are that its running time is independent of the size of the grid and number of line failures, and that it provides accurate information recovery under some conditions on the attacked area. Moreover, it approximately recovers the information and provides the confidence of the solution when these conditions do not hold.

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Cyber-Physical Attack-Resilient Wide-Area Monitoring, Protection, and Control for the Power Grid

Cited by 218 publications

References 45 publications

Impact of Cyber Attacks on High Voltage DC Transmission Damping Control

Impact of Cyber Attacks on High Voltage DC Transmission Damping Control

An Online Detection Framework for Cyber Attacks on Automatic Generation Control

EXPOSE the Line Failures Following a Cyber-Physical Attack on the Power Grid

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