Identification and Mitigation of Data Integrity Stealth Attacks in Frequency Regulation of Power Systems

Load frequency control (LFC) application in power systems has an essential role in improving the system’s stability. However, the presence of the automatic generation control service incorporated into the LFC application, being a system dependent on communication networks, makes the LFC system susceptible to cyber threats. Falsifying measurement and control signals through communication networks, known as data integrity attacks (DIAs), can severely affect the system’s dynamic performance. This paper studies the frequency regulation issue of an interconnected power system under stealth DIAs. Accordingly, a novel identification scheme consisting of the dynamic multiplicative watermarking technique, an estimator, an anomaly detector, and a trigger mechanism is introduced to identify the DIAs. The watermarking concept is the intentional overlay of a watermark signal onto the source signal transmitted through the communication network. Achieving this requires using a specific watermarking filter, and the result is that operators gain greater flexibility in regulating the transmitted signals, which in turn provides improved signal integrity. In the proposed identification scheme, there is a multiplicative superimposition, where the watermark equalizing filter on the opposite end of the network can cancel out the impact of the watermarking, leading to the retrieval of the original signal. After identifying the attack, the proposed trigger mechanism blocks the manipulated ACE signal and submits the estimated ACE signal to the secondary controller. A model-free sliding mode control method is also implemented as the secondary frequency controller to regulate the system’s frequency under DIAs, load disturbances, and physical limitations. The Speedgoat-based real-time simulation results reveal that the developed defense method can timely identify stealth DIAs and significantly improve the system’s dynamic responses compared to the other techniques under these attacks.

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Publication Details

Journal
IEEE Transactions on Information Forensics and Security
Published
2025-01-01
DOI
https://doi.org/10.1109/tifs.2025.3578922
Citations
6
Primary Topic
Smart Grid Security and Resilience
Type
article
Field-Weighted Citation Impact
7.29
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article

Identification and Mitigation of Data Integrity Stealth Attacks in Frequency Regulation of Power Systems

Esmaeil Mahboubi-Moghaddam, Soroush Oshnoei, Meysam Gheisarnejad, Mohammad Hassan Khooban et al.
6 citations
IEEE Transactions on Information Forensics and Security
Smart Grid Security and Resilience
7.29
article

Identification and Mitigation of Data Integrity Stealth Attacks in Frequency Regulation of Power Systems

Esmaeil Mahboubi-Moghaddam, Soroush Oshnoei, Meysam Gheisarnejad, Mohammad Hassan Khooban, Jalal Heidari
article en
6 citations

Abstract

Load frequency control (LFC) application in power systems has an essential role in improving the system’s stability. However, the presence of the automatic generation control service incorporated into the LFC application, being a system dependent on communication networks, makes the LFC system susceptible to cyber threats. Falsifying measurement and control signals through communication networks, known as data integrity attacks (DIAs), can severely affect the system’s dynamic performance. This paper studies the frequency regulation issue of an interconnected power system under stealth DIAs. Accordingly, a novel identification scheme consisting of the dynamic multiplicative watermarking technique, an estimator, an anomaly detector, and a trigger mechanism is introduced to identify the DIAs. The watermarking concept is the intentional overlay of a watermark signal onto the source signal transmitted through the communication network. Achieving this requires using a specific watermarking filter, and the result is that operators gain greater flexibility in regulating the transmitted signals, which in turn provides improved signal integrity. In the proposed identification scheme, there is a multiplicative superimposition, where the watermark equalizing filter on the opposite end of the network can cancel out the impact of the watermarking, leading to the retrieval of the original signal. After identifying the attack, the proposed trigger mechanism blocks the manipulated ACE signal and submits the estimated ACE signal to the secondary controller. A model-free sliding mode control method is also implemented as the secondary frequency controller to regulate the system’s frequency under DIAs, load disturbances, and physical limitations. The Speedgoat-based real-time simulation results reveal that the developed defense method can timely identify stealth DIAs and significantly improve the system’s dynamic responses compared to the other techniques under these attacks.

IEEE Transactions on Information Forensics and SecurityVol. 20
Université du Québec à Montréal (CA), Aarhus University (DK), Ghent University (BE), Quchan University of Advanced Technology (IR), École de Technologie Supérieure (CA)
Openalex Percentile: Top 3%
Smart Grid Security and Resilience
7.29
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