A Stealth Cyber-Attack Detection Strategy for DC Microgrids

Sahoo, Subham; Mishra, Sukumar; Peng, Jimmy Chih-Hsien; Dragičević, Tomislav

doi:10.1109/tpel.2018.2879886

Cited by 201 publications

(143 citation statements)

References 39 publications

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“…This is due to the fact that modern control systems are evermore exposed to cyber-attacks, given the increasing integration of physical and cyber resources in CPS control loops [14]. An area that has received specific attention because of its criticality has been the secure control and estimation of power networks, with specific focus on smart grids [9], [15], [16], [17], and microgrids [18], [19], [20], [21]. Among the works addressing the security problem in microgrids, [20], [21] offer techniques to detect cyber-attacks in DCmGs.…”

Section: State Of the Artmentioning

confidence: 99%

“…An area that has received specific attention because of its criticality has been the secure control and estimation of power networks, with specific focus on smart grids [9], [15], [16], [17], and microgrids [18], [19], [20], [21]. Among the works addressing the security problem in microgrids, [20], [21] offer techniques to detect cyber-attacks in DCmGs. In particular, the authors of [20] exploit Signal Temporal Logic (STL) to detect whether an attack is present, by verifying whether given STL requirements are violated.…”

Section: State Of the Artmentioning

confidence: 99%

“…In particular, the authors of [20] exploit Signal Temporal Logic (STL) to detect whether an attack is present, by verifying whether given STL requirements are violated. In [21], on the other hand, the authors consider "balanced" attacks, and define a Cooperative Vulnerability Factor (CVF) for detection, exploiting secure knowledge of control inputs of neighboring DGUs.…”

Section: State Of the Artmentioning

confidence: 99%

See 2 more Smart Citations

A Distributed Cyber-Attack Detection Scheme With Application to DC Microgrids

Gallo

Turan

Boem

et al. 2020

IEEE Trans. Automat. Contr.

130

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DC microgrids often present a hierarchical control architecture, requiring integration of communication layers. This leads to the possibility of malicious attackers disrupting the overall system. Motivated by this application, in this paper we present a distributed monitoring scheme to provide attackdetection capabilities for linear Large-Scale Systems. The proposed architecture relies on a Luenberger observer together with a bank of Unknown-Intput Observers (UIOs) at each subsystem, providing attack detection capabilities. We describe the architecture and analyze conditions under which attacks are guaranteed to be detected, and, conversely, when they are stealthy. Our analysis shows that some classes of attacks cannot be detected using either module independently; rather, by exploiting both modules simultaneously, we are able to improve the detection properties of the diagnostic tool as a whole. Theoretical results are backed up by simulations, where our method is applied to a realistic model of a low-voltage DC microgrid under attack.

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Section: State Of the Artmentioning

confidence: 99%

Section: State Of the Artmentioning

confidence: 99%

Section: State Of the Artmentioning

confidence: 99%

See 1 more Smart Citation

A Distributed Cyber-Attack Detection Scheme With Application to DC Microgrids

Gallo

Turan

Boem

et al. 2020

IEEE Trans. Automat. Contr.

130

View full text Add to dashboard Cite

show abstract

“…In [4], a secure information flow framework was developed for 118-bus distribution network with power electronics driven HVAC system. In [8], a physicsbased, cooperative mechanism was developed to detect stealthy attacks in DC microgrids with a number of DC-DC converters, which can bypass most of observer-based detection methods. In [9], a physics-based framework to detect false-data injection attacks in DC microgrids with a number of DC-DC converters.…”

Section: Introductionmentioning

confidence: 99%

Detection and Identification of Cyber and Physical Attacks on Distribution Power Grids With PVs: An Online High-Dimensional Data-Driven Approach

Xie

Yang

et al. 2022

IEEE J. Emerg. Sel. Topics Power Electron.

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Cyber and physical attacks threaten the security of distribution power grids. The emerging renewable energy sources such as photovoltaics (PVs) introduce new potential vulnerabilities. Based on the electric waveform data measured by waveform sensors in the distribution power networks, in this paper, we propose a novel high-dimensional data-driven cyber physical attack detection and identification approach (HCADI). Firstly, we analyze the cyber and physical attack impacts (including cyber attacks on the solar inverter causing unusual harmonics) on electric waveforms in distribution power grids. Then, we construct a high dimensional streaming data feature matrix based on signal analysis of multiple sensors in the network. Next, we propose a novel mechanism including leverage score based attack detection and binary matrix factorization based attack diagnosis. By leveraging the data structure and binary coding, our HCADI approach does not need the training stage for both detection and the root cause diagnosis, which is needed for machine learning/deep learning-based methods. To the best of our knowledge, it is the first attempt to use raw electrical waveform data to detect and identify the power electronics cyber/physical attacks in distribution power grids with PVs.

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“…A signal temporal logic detection method is proposed in [6] for effectively detect, locate and qualify attack. In [7], a cooperative vulnerability factor (CVF) framework is introduced for each agent, and the positive value of CVF represents that the agent is attacked. A software-defined networking communication architecture and a secure network of assured power enclaves are respectively proposed in [8][9] to enhance the attack resistance of microgrid.…”

Section: Introductionmentioning

confidence: 99%

Distributed Control for AC Microgrids with False Data Injection Attacks and Time Delays

Wang

2020

E3S Web Conf.

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Distributed control is widely used in AC microgrids to maintain frequency and voltage stability and internal power balance. However, distributed control need realizes information interaction through communication network, which makes microgrid vulnerable to network attack. A distributed control strategy based on consensus theory is proposed in this paper to enhance the resilience of microgrid to attack. An attack detection and localization method is designed for the false data injection attack. The Artstein’s transformation is introduced to process the delay data and the performance of controller under delay can be enhanced. An isolated island AC microgrid model was built in Simulink platform for simulation to verify the performance of the controller. The simulation results verified the effectiveness of the control strategy against false data injection attack and time delay.

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A Stealth Cyber-Attack Detection Strategy for DC Microgrids

Cited by 201 publications

References 39 publications

A Distributed Cyber-Attack Detection Scheme With Application to DC Microgrids

A Distributed Cyber-Attack Detection Scheme With Application to DC Microgrids

Detection and Identification of Cyber and Physical Attacks on Distribution Power Grids With PVs: An Online High-Dimensional Data-Driven Approach

Distributed Control for AC Microgrids with False Data Injection Attacks and Time Delays

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