An Ensemble Learning-Based Cyber-Attacks Detection Method of Cyber-Physical Power Systems
Author:
Affiliation:
1. Zhejiang University,National Laboratory of Industrial Control Technology, Institute of Cyber-Systems and Control,Hangzhou,China,310027
Funder
National Natural Science Foundation of China
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9959088/9959097/09959185.pdf?arnumber=9959185
Reference27 articles.
1. Online false data injection attack detection with wavelet transform and deep neural networks;james;IEEE Transactions on Industrial Informatics,2018
2. Locational Detection of the False Data Injection Attack in a Smart Grid: A Multilabel Classification Approach
3. Ensemble Classification and Regression-Recent Developments, Applications and Future Directions [Review Article]
4. EnLSTM-WPEO: Short-Term Traffic Flow Prediction by Ensemble LSTM, NNCT Weight Integration, and Population Extremal Optimization
5. An ensemble of decision trees with random vector functional link networks for multi-class classification
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3. Exploration of Ensemble Methods for Cyber Attack Detection in Cyber-Physical Systems;IFIP Advances in Information and Communication Technology;2024
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