A novel Machine Learning-based Network Intrusion Detection System for Software-Defined Network
Author:
Affiliation:
1. School of Information and Communication Technology, Hanoi University of Science and Technology,Hanoi,Vietnam
Funder
Vietnam National Foundation for Science and Technology Development (NAFOSTED)
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9335828/9335829/09335863.pdf?arnumber=9335863
Cited by 6 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. Trustable Network Intrusion Detection System through Wisdomnet and Uncertainty Measures;2024 IEEE 49th Conference on Local Computer Networks (LCN);2024-10-08
2. A Novel Lightweight NIDS Framework for Detecting Anomalous Data Traffic in Contemporary Networks;Journal of Circuits, Systems and Computers;2024-03-11
3. Exploring Traffic Patterns Through Network Programmability: Introducing SDNFLow, a Comprehensive OpenFlow-Based Statistics Dataset for Attack Detection;IEEE Access;2024
4. Network intrusion detection system using ML;i-manager’s Journal on Wireless Communication Networks;2024
5. Comparative Analysis of 1D-CNN and 2D-CNN for Network Intrusion Detection in Software Defined Networks;Lecture Notes on Data Engineering and Communications Technologies;2024
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