TMG-GAN: Generative Adversarial Networks-Based Imbalanced Learning for Network Intrusion Detection
Author:
Affiliation:
1. School of Cyber Science and Engineering, Wuhan University, Wuhan, China
2. School of Computing, National University of Singapore, Cluny Road, Singapore
Funder
Operation Wise Eyes
Key Research and Development Projects in Hubei Province
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Computer Networks and Communications,Safety, Risk, Reliability and Quality
Link
http://xplorestaging.ieee.org/ielx7/10206/10319981/10312801.pdf?arnumber=10312801
Reference33 articles.
1. Fast Anomaly Identification Based on Multi-Aspect Data Streams for Intelligent Intrusion Detection Toward Secure Industry 4.0
2. Dependable Intrusion Detection System for IoT: A Deep Transfer Learning Based Approach
3. A Method of Few-Shot Network Intrusion Detection Based on Meta-Learning Framework
4. Dendron : Genetic trees driven rule induction for network intrusion detection systems
5. Features Dimensionality Reduction Approaches for Machine Learning Based Network Intrusion Detection
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