Detecting Cyber-Physical-Attacks in AC microgrids using artificial neural networks
Author:
Funder
European INTERREG-V
Freiburg University, Germany
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9575168/9576159/09576466.pdf?arnumber=9576466
Cited by 5 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. Cyber–physical anomaly detection for inverter-based microgrid using autoencoder neural network;Applied Energy;2024-02
2. False Data Injection Attack Detection and Mitigation Using Nonlinear Autoregressive Exogenous Input-Based Observers in Distributed Control for DC Microgrid;IEEE Open Journal of the Industrial Electronics Society;2024
3. Enhancing Security in Islanded AC Microgrid: Detecting and Mitigating FDI Attacks in Secondary Consensus Control through AI-Based Method;2023 IEEE International Conference on Energy Technologies for Future Grids (ETFG);2023-12-03
4. LSTM Networks for Cyber-physical Attack Diagnoses in Microgrids;2023 IEEE 32nd International Symposium on Industrial Electronics (ISIE);2023-06-19
5. Experimental HIl implementation of RNN for detecting cyber physical attacks in AC microgrids;2022 International Symposium on Power Electronics, Electrical Drives, Automation and Motion (SPEEDAM);2022-06-22
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