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.
Matthieu MouyartGuilherme Medeiros MachadoJae-Yun JunPublished in: J. Sens. Actuator Networks (2023)
Keyphrases
- generative model
- intrusion detection system
- reinforcement learning
- multi agent
- intrusion detection
- network security
- probabilistic model
- distributed intrusion detection
- computer networks
- network intrusion detection
- anomaly detection
- network traffic
- prior knowledge
- bayesian framework
- em algorithm
- network traffic data
- state space
- attack detection
- discriminative models
- multiple agents
- machine learning
- optimal policy
- latent dirichlet allocation
- markov decision processes
- topic models
- databases
- computer systems
- data mining
- unsupervised learning
- expectation maximization
- supervised learning
- alert correlation
- generative and discriminative models
- data processing
- knowledge discovery
- dirichlet process mixture models
- misuse detection