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Deep Reinforcement Learning for IDS by darkthings457 is a document available to read on EtoBox.

What is Deep Reinforcement Learning for IDS about?

The paper presents a novel network intrusion detection system utilizing Deep Reinforcement Learning (DRL) and a Deep Q-Learning (DQL) model, achieving an accuracy of 91.4% in detecting various types of intrusions. The proposed system continuously learns and improves its detection capabilities through automated trial-and-error methods, outperforming traditional machine learning models. Experimental results indicate that the DQL model effectively classifies network intrusions with high precision and recall ra

Author

darkthings457

Language

EN