A Multi-Agent Intrusion Detection System Optimized by a Deep Reinforcement Learning Approach with a Dataset Enlarged Using a Generative Model to Reduce the Bias Effect

A Multi-Agent Intrusion Detection System Optimized by a Deep Reinforcement Learning Approach with a Dataset Enlarged Using a Generative Model to Reduce the Bias Effect

Intrusion detection systems can defectively perform when they are adjusted with datasets that are unbalanced in terms of attack data and non-attack data. Most datasets contain more non-attack data than attack data, and this circumstance can introduce biases in intrusion detection systems, making the...

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Bibliographic Details
Main Authors: Matthieu Mouyart, Guilherme Medeiros Machado, Jae-Yun Jun
Format: Article
Language:English
Published: MDPI AG 2023-09-01
Series:Journal of Sensor and Actuator Networks
Subjects:
cybersecurity
intrusion detection
insider threat
multi-agent system
generative adversarial network
deep reinforcement learning
Online Access:https://www.mdpi.com/2224-2708/12/5/68

Internet

https://www.mdpi.com/2224-2708/12/5/68

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