An Incremental Majority Voting Approach for Intrusion Detection System Based on Machine Learning
Author:
Affiliation:
1. Department of Computer and Information Security, and Convergence Engineering for Intelligent Drone, Sejong University, Seoul, South Korea
2. Department of Computer and Information Security, Sejong University, Seoul, South Korea
Funder
National Research Foundation of Korea
Ministry of Education
NRF
Ministry of Science and ICT
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Link
http://xplorestaging.ieee.org/ielx7/6287639/10380310/10418218.pdf?arnumber=10418218
Reference38 articles.
1. Exploring the Top Five Evolving Threats in Cybersecurity: An In-Depth Overview
2. Evolution of the cyber security threat: An overview of the scale of cyber threat;Fadziso;Digitalization Sustainability Rev.,2023
3. Cyber Security
4. A Study of Network Intrusion Detection Systems Using Artificial Intelligence/Machine Learning
5. Cyber-Attack Prediction Based on Network Intrusion Detection Systems for Alert Correlation Techniques: A Survey
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1. Comparison of Supervised Machine Learning Algorithms with Bagged-Ensemble Method for Intrusion Detection;2024 IEEE Students Conference on Engineering and Systems (SCES);2024-06-21
2. Voting Ensemble: Performance Improvement for Intrusion Detection System;2024 3rd International Conference on Artificial Intelligence For Internet of Things (AIIoT);2024-05-03
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