{"title":"电力系统调频中数据完整性隐身攻击的识别与缓解","authors":"Soroush Oshnoei;Jalal Heidari;Esmaeil Mahboubi-Moghaddam;Meysam Gheisarnejad;Mohammad-Hassan Khooban","doi":"10.1109/TIFS.2025.3578922","DOIUrl":null,"url":null,"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.","PeriodicalId":13492,"journal":{"name":"IEEE Transactions on Information Forensics and Security","volume":"20 ","pages":"6133-6148"},"PeriodicalIF":8.0000,"publicationDate":"2025-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Identification and Mitigation of Data Integrity Stealth Attacks in Frequency Regulation of Power Systems\",\"authors\":\"Soroush Oshnoei;Jalal Heidari;Esmaeil Mahboubi-Moghaddam;Meysam Gheisarnejad;Mohammad-Hassan Khooban\",\"doi\":\"10.1109/TIFS.2025.3578922\",\"DOIUrl\":null,\"url\":null,\"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.\",\"PeriodicalId\":13492,\"journal\":{\"name\":\"IEEE Transactions on Information Forensics and Security\",\"volume\":\"20 \",\"pages\":\"6133-6148\"},\"PeriodicalIF\":8.0000,\"publicationDate\":\"2025-06-11\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE Transactions on Information Forensics and Security\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://ieeexplore.ieee.org/document/11030727/\",\"RegionNum\":1,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"COMPUTER SCIENCE, THEORY & METHODS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Transactions on Information Forensics and Security","FirstCategoryId":"94","ListUrlMain":"https://ieeexplore.ieee.org/document/11030727/","RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, THEORY & METHODS","Score":null,"Total":0}
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.
期刊介绍:
The IEEE Transactions on Information Forensics and Security covers the sciences, technologies, and applications relating to information forensics, information security, biometrics, surveillance and systems applications that incorporate these features