A Sequential Supervised Machine Learning Approach for Cyber Attack Detection in a Smart Grid System
Author:
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9654273/9654259/09654767.pdf?arnumber=9654767
Cited by 21 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. Review of Intrusion Detection System for Prediction of Cyber Attacks using AI Techniques;International Journal of Scientific Research in Computer Science, Engineering and Information Technology;2024-08-16
2. ByteStack-ID: Integrated Stacked Model Leveraging Payload Byte Frequency for Grayscale Image-based Network Intrusion Detection;ICC 2024 - IEEE International Conference on Communications;2024-06-09
3. Smart grid cyberattack types classification: A fine tree bagging-based ensemble learning approach with feature selection;Sustainable Energy, Grids and Networks;2024-06
4. False Data Injection Attacks Detection in Wide Area Damping Control System Using Semi-Supervised Generative Adversarial Network Model;2024 IEEE Power & Energy Society Innovative Smart Grid Technologies Conference (ISGT);2024-02-19
5. Stacking-based multi-objective approach for detection of smart power grid attacks using evolutionary ensemble learning;International Journal of Critical Infrastructures;2024
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