False Data Attacks Against AC State Estimation With Incomplete Network Information

Liu, Xuan; Li, Zuyi

doi:10.1109/tsg.2016.2521178

Cited by 210 publications

(104 citation statements)

References 16 publications

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“…In this section, the proposed approach is applied and investigated on the IEEE 14-bus test grid. This test grid is often used in the context of FDI attack detection [27], [29], [30] and attack construction [35], [38]. The voltage angles and magnitudes of this grid are calculated from the AC power flow solver implemented by the pandapower-tool [55].…”

Section: Case Studymentioning

confidence: 99%

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Detection of False Data Injection Attacks in Smart Grids Based on Graph Signal Processing

Drayer

Routtenberg

2020

IEEE Systems Journal

112

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Section: Case Studymentioning

confidence: 99%

“…Nevertheless, several contributions that show how an attacker could construct undetectable attacks based on the AC model do exist (see, e.g. [11], [27], [37], [38]).…”

mentioning

confidence: 99%

Detection of False Data Injection Attacks in Smart Grids Based on Graph Signal Processing

Drayer

Routtenberg

2020

IEEE Systems Journal

112

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“…Consequently, the FDI attack is successfully applied to the measurement vector when the attack is modelled as a Hc  . In this case, the measurement vector under the attack has a larger deviation from the true vector, which will undermine the safe and stable operation of generators [28].…”

Section: Generator Modelmentioning

confidence: 99%

Dynamic State Estimation of Generators Under Cyber Attacks

Yang

Liang

2019

IEEE Access

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Accurate and reliable estimation of generator's dynamic state vectors in real time are critical to the monitoring and control of power systems. A robust Cubature Kalman Filter (RCKF) based approach is proposed for dynamic state estimation (DSE) of generators under cyber attacks in this paper. First, two types of cyber attacks, namely false data injection and denial of service attacks, are modelled and thereby introduced into DSE of a generator by mixing the attack vectors with the measurement data; Second, under cyber attacks with different degrees of sophistication, the RCKF algorithm and the Cubature Kalman Filter (CKF) algorithm are adopted to the DSE, and then the two algorithms are compared and discussed. The novelty of this study lies primarily in our attempt to introduce cyber attacks into DSE of generators. The simulation results on the IEEE 9-bus system and the New England 16-machine 68-bus system verify the effectiveness and superiority of the RCKF. INDEX TERMS Dynamic state estimation, cyber attacks, false data injection, denial of service, generator, robust cubature Kalman filter, PMU data

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“…Furthermore, a numerous attacks of different categories such as Denial of Service (DoS) may perpetrate entire grid or any specific point of its components to disrupt grid main functions and make the service unstable or unavailable . False data injection attacks lead to compromise the data integrity between grid components . Additionally, existing vulnerabilities in smart grid devices may allow attackers to access the network, break the confidentiality and integrity of transmitted data.…”

Section: Introductionmentioning

confidence: 99%

“…15 False data injection attacks lead to compromise the data integrity between grid components. 16 Additionally, existing vulnerabilities in smart grid devices may allow attackers to access the network, break the confidentiality and integrity of transmitted data. Among these types of threats in smart grid, DoS is a typical attack that severely threatens the availability of interconnected grid components and disrupts a crucial service to millions of citizens.…”

Section: Introductionmentioning

confidence: 99%

PYGRID: A software development and assessment framework for grid‐aware software defined networking

et al. 2018

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The Internet of Things (IoT) envisions to connect Advanced Metering Infrastructure (AMI) to the Internet to facilitate efficient resource management in smart cities. Smart grid is the evolutionary approach towards a more dynamic, situation‐aware, and elastic power systems in smart cities. However, due to the huge scale, heterogeneity and complexity of the many interconnected cyber and physical devices, current network and security technologies are incapable of best serving these needs. Destructive attacks targeting these components such as Denial of Service (DoS) may fully use grid structure and disrupt its crucial service. Recent researches offer the use of modern Software Defined Networking (SDN) to solve synonymous Cyber Physical Systems (CPS) network and security challenges. These researches noted the lack of an adequate platform to simulate grid systems network infrastructure. Therefore, in this paper, we present PYGRID, a software development and assessment framework for grid‐aware SDN. Additionally, a top level SDN application is developed in SDN‐enabled smart grid network to demonstrate the effectiveness of such merger and to mitigate DoS attacks. PYGRID is developed using PYTHON, an OSI‐approved open source language considering standard client and server industrial communication protocols. IEEE 14‐bus power system is adopted to demonstrate the potent and effectiveness of the proposed solution. We conducted multiple experiments to validate the developed framework over 14‐bus system using PYPOWER. To the best of our knowledge, the resulted platform may be considered the first completely open source implementation of a secure SDN enabled smart grid simulator.

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False Data Attacks Against AC State Estimation With Incomplete Network Information

Cited by 210 publications

References 16 publications

Detection of False Data Injection Attacks in Smart Grids Based on Graph Signal Processing

Detection of False Data Injection Attacks in Smart Grids Based on Graph Signal Processing

Dynamic State Estimation of Generators Under Cyber Attacks

PYGRID: A software development and assessment framework for grid‐aware software defined networking

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