A Survey of Reinforcement Learning in Intrusion Detection
Author:
Affiliation:
1. Georgia Southern University,Mathematical Sciences,Savannah,GA,USA
2. University of South Florida,Mathematics and Statistics,Tampa,FL,USA
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9896867/9896960/09897058.pdf?arnumber=9897058
Reference42 articles.
1. Adversarial muti-agent reinforcement learning algorithm for anomaly network intrusion detection systems;mohamed;International Journal on Information Technologies & Security ? 3,2021
2. Deep Reinforcement Learning-Based Traffic Sampling for Multiple Traffic Analyzers on Software-Defined Networks
3. Designing online network intrusion detection using deep auto-encoder Q-learning
4. A deep‐learning‐ and reinforcement‐learning‐based system for encrypted network malicious traffic detection
5. A Deep Reinforcement Learning Approach for Anomaly Network Intrusion Detection System
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1. Deep Reinforcement Learning-based Malicious URL Detection with Feature Selection;2024 IEEE 3rd International Conference on AI in Cybersecurity (ICAIC);2024-02-07
2. Impact of Machine Learning in Cybersecurity: A Critical Review with Insights on the Internet of Things;Lecture Notes in Networks and Systems;2024
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