Reinforcement Learning-Based Detection for State Estimation Under False Data Injection

doi:10.1109/ACCESS.2021.3076538

Reinforcement Learning-Based Detection for State Estimation Under False Data Injection

2021-01-01

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DOI：10.1109/ACCESS.2021.3076538

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We consider the problem of network security under false data injection attacks over wireless sensor networks.To resist the attacks which can inject false data into communication channels according to a certain probability, we formulate the online attack detection problem as a partially observable Markov decision process problem and design a detector for each sensor based on the framework of model-free reinforcement learning. By numerical simulations, we illustrate the effectiveness of the proposed reinforcement learning algorithm and show the performance of the proposed detector compared with the typical detector in the existing works.

Keywords:

Detectors

Reinforcement learning

Technological innovation

Wireless sensor networks

Smart grids

Markov processes

Image edge detection

Wireless sensor network

false data injection attack

reinforcement learning

partially observable Markov decision process

Reinforcement Learning-Based Detection for State Estimation Under False Data Injection

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