Power System Security Under False Data Injection Attacks With Exploitation and Exploration Based on Reinforcement Learning

Power System Security Under False Data Injection Attacks With Exploitation and Exploration Based on Reinforcement Learning

The false data injection (FDI) attack is a potential threat to the security of smart grids, and therefore, such threats should be assessed carefully. This paper proposes a self-governing FDI attack method with exploitation and exploration mechanisms and then evaluates its threat to power systems. Th...

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Bibliographic Details
Main Authors: Zhisheng Wang, Ying Chen, Feng Liu, Yue Xia, Xuemin Zhang
Format: Article
Language:English
Published: IEEE 2018-01-01
Series:IEEE Access
Subjects:
Cybersecurity
false data injection
partially observable Markov decision process
nearest sequence memory Q-learning
Online Access:https://ieeexplore.ieee.org/document/8429074/

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