ACapsule Q-Learning Based Reinforcement Model for Intrusion Detection System on Smart Grid
Author:
Affiliation:
1. School of Computer Science and Electrical Engineering, University of North Dakota,Grand Forks,ND,58201
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10187212/10187216/10187374.pdf?arnumber=10187374
Reference26 articles.
1. Unsupervised Machine Learning-Based Detection of Covert Data Integrity Assault in Smart Grid Networks Utilizing Isolation Forest
2. FDI attack detection using extra trees algorithm and deep learning algorithm-autoencoder in smart grid
3. Network Intrusion Detection Systems Using Adversarial Reinforcement Learning with Deep Q-network
4. A Deep Reinforcement Learning Approach for Anomaly Network Intrusion Detection System
5. A Comparative Analysis of Supervised and Unsupervised Models for Detecting Attacks on the Intrusion Detection Systems
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