Please use this identifier to cite or link to this item: http://localhost/handle/Hannan/223242
Title: Optimal Protection Strategy Against False Data Injection Attacks in Power Systems
Authors: Xuan Liu;Zhiyi Li;Zuyi Li
Year: 2017
Publisher: IEEE
Abstract: It was revealed that modern power systems are at high risk of cyber-attacks, as an attacker can stealthily execute false data injection attacks against the state estimation without knowing the full topology and parameter information of the entire power network. To mitigate the risk, in this paper, we propose a bilevel mixed integer linear programming (MILP) model to determine the least number of measurements to be protected. A decomposition approach is adopted to obtain the suboptimal solution. To further reduce the computation complexity, we also propose to separate the power grid into several subnetworks using a MILP approach and apply distributed protection strategy to each subnetwork. The simulations on the IEEE 14-bus, IEEE 24-bus, IEEE 30-bus, and IEEE 118-bus systems verify the correctness and effectiveness of the proposed protection strategy.
URI: http://localhost/handle/Hannan/223242
volume: 8
issue: 4
More Information: 1802,
1810
Appears in Collections:2017

Files in This Item:
File SizeFormat 
7370787.pdf670.76 kBAdobe PDF
Title: Optimal Protection Strategy Against False Data Injection Attacks in Power Systems
Authors: Xuan Liu;Zhiyi Li;Zuyi Li
Year: 2017
Publisher: IEEE
Abstract: It was revealed that modern power systems are at high risk of cyber-attacks, as an attacker can stealthily execute false data injection attacks against the state estimation without knowing the full topology and parameter information of the entire power network. To mitigate the risk, in this paper, we propose a bilevel mixed integer linear programming (MILP) model to determine the least number of measurements to be protected. A decomposition approach is adopted to obtain the suboptimal solution. To further reduce the computation complexity, we also propose to separate the power grid into several subnetworks using a MILP approach and apply distributed protection strategy to each subnetwork. The simulations on the IEEE 14-bus, IEEE 24-bus, IEEE 30-bus, and IEEE 118-bus systems verify the correctness and effectiveness of the proposed protection strategy.
URI: http://localhost/handle/Hannan/223242
volume: 8
issue: 4
More Information: 1802,
1810
Appears in Collections:2017

Files in This Item:
File SizeFormat 
7370787.pdf670.76 kBAdobe PDF
Title: Optimal Protection Strategy Against False Data Injection Attacks in Power Systems
Authors: Xuan Liu;Zhiyi Li;Zuyi Li
Year: 2017
Publisher: IEEE
Abstract: It was revealed that modern power systems are at high risk of cyber-attacks, as an attacker can stealthily execute false data injection attacks against the state estimation without knowing the full topology and parameter information of the entire power network. To mitigate the risk, in this paper, we propose a bilevel mixed integer linear programming (MILP) model to determine the least number of measurements to be protected. A decomposition approach is adopted to obtain the suboptimal solution. To further reduce the computation complexity, we also propose to separate the power grid into several subnetworks using a MILP approach and apply distributed protection strategy to each subnetwork. The simulations on the IEEE 14-bus, IEEE 24-bus, IEEE 30-bus, and IEEE 118-bus systems verify the correctness and effectiveness of the proposed protection strategy.
URI: http://localhost/handle/Hannan/223242
volume: 8
issue: 4
More Information: 1802,
1810
Appears in Collections:2017

Files in This Item:
File SizeFormat 
7370787.pdf670.76 kBAdobe PDF