Defending Against Data Integrity Attacks in Smart Grid: A Deep Reinforcement Learning-Based Approach

Defending Against Data Integrity Attacks in Smart Grid: A Deep Reinforcement Learning-Based Approach

State estimation plays a critical role in monitoring and managing operation of smart grid. Nonetheless, recent research efforts demonstrate that data integrity attacks are able to bypass the bad data detection mechanism and make the system operator obtain the misleading states of system, leading to...

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Bibliographic Details
Main Authors: Dou An, Qingyu Yang, Wenmao Liu, Yang Zhang
Format: Article
Language:English
Published: IEEE 2019-01-01
Series:IEEE Access
Subjects:
Cyber-physical systems
smart grid
data integrity attacks
deep reinforcement learning
Q-learning
Online Access:https://ieeexplore.ieee.org/document/8786811/

Internet

https://ieeexplore.ieee.org/document/8786811/

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