Limiting false data attacks on power system state estimation

Kosut, Oliver; Jia, Lei; Thomas, Robert J.; Tong, Lang

doi:10.1109/ciss.2010.5464816

Cited by 140 publications

(89 citation statements)

References 6 publications

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“…A number of recent studies have exploited the FDI attacks on power system state estimation and defense mechanisms, including detection-based methods (e.g. [5][6][7]) and protection-based methods (e.g. [8][9][10][11][12][13][14][15][16]).…”

Section: Introductionmentioning

confidence: 99%

PMU Placement in Electric Transmission Networks for Reliable State Estimation Against False Data Injection Attacks

Yang

Jiang

Hao

et al. 2017

IEEE Internet Things J.

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Abstract-Currently the false data injection (FDI) attack bring direct challenges in synchronized phase measurement unit (PMU) based network state estimation in wide-area measurement system (WAMS), resulting in degraded system reliability and power supply security. This paper assesses the performance of state estimation in electric cyber-physical system (ECPS) paradigm considering the presence of FDI attacks. The adverse impact on network state estimation is evaluated through simulations for a range of FDI attack scenarios using IEEE 14-bus network model. In addition, an algorithmic solution is proposed to address the issue of additional PMU installation and placement with cyber security consideration and evaluated for a set of standard electric transmission networks (IEEE 14-bus, 30-bus and 57-bus network). The numerical result confirms that the FDI attack can significantly degrade the state estimation and the cyber security can be improved by an appropriate placement of a limited number of additional PMUs. Index Terms-Phase

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Section: Introductionmentioning

confidence: 99%

PMU Placement in Electric Transmission Networks for Reliable State Estimation Against False Data Injection Attacks

Yang

Jiang

Hao

et al. 2017

IEEE Internet Things J.

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“…Therefore, we extend our prior work in [8] to develop a more practical technique based on l 1 norm minimization. This is based on the well-known nature of the l 1 norm as a heuristic to find sparse solutions to optimization problems.…”

Section: A Summary Of Results and Contributionsmentioning

confidence: 99%

“…Because the adversary can choose where to attack the network and design the injected data, the problem of detecting malicious data cannot be formulated as a simple hypothesis test, and the uniformly most powerful test does not exist in general. We study a detector based on the generalized likelihood ratio test (GLRT) that was originally introduced in our prior work [8]. GLRT is not optimal in general, but it is known to perform well in practice and it has well established asymptotic optimality [9], [10], [11].…”

Section: A Summary Of Results and Contributionsmentioning

confidence: 99%

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Malicious Data Attacks on Smart Grid State Estimation: Attack Strategies and Countermeasures

Kosut

Jia

Thomas

et al. 2010

2010 First IEEE International Conference on Smart Grid Communications

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288

196

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Abstract-The problem of constructing malicious data attack of smart grid state estimation is considered together with countermeasures that detect the presence of such attacks. For the adversary, using a graph theoretic approach, an efficient algorithm with polynomial-time complexity is obtained for the design of unobservable malicious data attacks. When the unobservable attack does not exist due to restrictions of meter access, attacks are constructed to minimize the residue energy of attack while guaranteeing a certain level of increase of mean square error. For the control center, a computationally efficient algorithm is derived to detect and localize attacks using the generalized likelihood ratio test regularized by an L1 norm penalty on the strength of attack.

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“…An undetectable false data injection attack motivates a Bayesian framework, which was first proposed in Kosut et al [6]. The historical data can be used by the control center to track its belief state of the power system.…”

Section: Related Workmentioning

confidence: 99%

Protection Strategies Against False Data Injection Attacks with Uncertain Information on Electric Power Grids

Bae¹,

Lee²,

Kim³

et al. 2017

Journal of Electrical Engineering and Technology

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-False data injection attacks have recently been introduced as one of important issues related to cyber-attacks on electric power grids. These attacks aim to compromise the readings of multiple power meters in order to mislead the operation and control centers. Recent studies have shown that if a malicious attacker has complete knowledge of the power grid topology and branch admittances, s/he can adjust the false data injection attack such that the attack remains undetected and successfully passes the bad data detection tests that are used in power system state estimation. In this paper, we investigate that a practical false data injection attack is essentially a cyber-attack with uncertain information due to the attackers lack of knowledge with respect to the power grid parameters because the attacker has limited physical access to electric facilities and limited resources to compromise meters. We mathematically formulated a method of identifying the most vulnerable locations to false data injection attack. Furthermore, we suggest minimum topology changes or phasor measurement units (PMUs) installation in the given power grids for mitigating such attacks and indicate a new security metrics that can compare different power grid topologies. The proposed metrics for performance is verified in standard IEEE 30-bus system. We show that the robustness of grids can be improved dramatically with minimum topology changes and low cost.

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Limiting false data attacks on power system state estimation

Cited by 140 publications

References 6 publications

PMU Placement in Electric Transmission Networks for Reliable State Estimation Against False Data Injection Attacks

PMU Placement in Electric Transmission Networks for Reliable State Estimation Against False Data Injection Attacks

Malicious Data Attacks on Smart Grid State Estimation: Attack Strategies and Countermeasures

Protection Strategies Against False Data Injection Attacks with Uncertain Information on Electric Power Grids

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