Performance of Intrusion Detection System Using Bagging Ensemble with SDN-Base Classifier
Author:
Affiliation:
1. Universitas Gadjah Mada,Dept. of Electrical Engineering and Information Technology,Yogyakarta,Indonesia
Funder
Ministry of Finance
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9971149/9971157/09971334.pdf?arnumber=9971334
Reference37 articles.
1. Cyber intrusion detection by combined feature selection algorithm
2. Intrusion detection based on genetic fuzzy classification system
3. Random Forest Modeling for Network Intrusion Detection System
4. A Novel Intrusion Detection System Based on Advanced Naive Bayesian Classification
5. The Measurement of Observer Agreement for Categorical Data
Cited by 4 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. B-DT Model: A Derivative Ensemble Method to Improve Performance of Intrusion Detection System;Journal of Advances in Information Technology;2024
2. Deep Learning Model for Intrusion Detection in SDN Networks;2023 1st International Conference on Optimization Techniques for Learning (ICOTL);2023-12-07
3. A Comprehensive Survey on Ensemble Learning-Based Intrusion Detection Approaches in Computer Networks;IEEE Access;2023
4. New Approach of Ensemble Method to Improve Performance of IDS using S-SDN Classifier;2022 IEEE International Conference on Communication, Networks and Satellite (COMNETSAT);2022-11-03
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