Effective Features Selection and Machine Learning Classifiers for Improved Wireless Intrusion Detection
Author:
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/8511028/8530880/08530969.pdf?arnumber=8530969
Cited by 10 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. Improving Network Intrusion Detection Using Supervised Learning for Feature Selection;2023 IEEE/ACIS 8th International Conference on Big Data, Cloud Computing, and Data Science (BCD);2023-12-14
2. A Systematic Review on Intrusion Detection System in Wireless Networks: Variants, Attacks, and Applications;Wireless Personal Communications;2023-11
3. Fusion of Feature Selection Techniques and Machine learning Algorithms for Attack Classification on 802.11 Wi-Fi AWID Dataset;2023 IEEE Guwahati Subsection Conference (GCON);2023-06-23
4. Hybrid intelligent intrusion detection system for multiple Wi‐Fi attacks in wireless networks using stacked restricted Boltzmann machine and deep belief networks;Concurrency and Computation: Practice and Experience;2023-05-18
5. Machine Learning-Driven Algorithms for Network Anomaly Detection;Inventive Computation and Information Technologies;2022
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