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In this paper, we propose a reinforcement learning based vulnerability analysis scheme for data injection attack without relying on the power system topology.
In this paper, we propose a deep reinforcement learning based vulnerability analysis scheme for smart grids that enables the control center to construct an ...
In this study, we proposed an attention-based deep reinforcement learning detection model (Attention-DRLD) to detect FDIAs in smart grid.
Nov 24, 2022 · In this paper, we propose a deep reinforcement learning based vulnerability analysis scheme for smart grids that enables the control center to construct an ...
This paper proposed a false data injection attack model and countering detection methods based on deep reinforcement learning (DRL).
Nov 17, 2022 · In this paper, we propose a deep reinforcement learning based vulnerability analysis scheme for smart grids that enables the control center to construct an ...
Reinforcement Learning Based Vulnerability Analysis for Smart Grids Against False Data Injection Attacks. Chapter. Nov 2022. Shiyu Xu · Shi Yu · Liang ...
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The data injection attack vector is critical to vulnerability analysis that determines the probability of successful vulner- ability detection and the injected ...
Abstract—The dependence on advanced information and com- munication technology increases the vulnerability in smart grids under cyber-attacks.
The primary goal of this paper is to show the impact of an FDIA attack on a power dataset and to use machine learning algorithms to detect the attack; to ...
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