Developing a hybrid feature selection method to detect botnet attacks in IoT devices-Reference-Cited by-同舟云学术

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Developing a hybrid feature selection method to detect botnet attacks in IoT devices

Published:2024-07 Issue:3 Volume:51 Page:100222
ISSN:2307-4108
Container-title:Kuwait Journal of Science
language:en
Short-container-title:Kuwait Journal of Science

Author:

Alshaeaa Hyder Yahya^ORCID,Ghadhban Zainab Mohammed

Publisher

Elsevier BV

Reference50 articles.

1. An efficient network intrusion detection and classification system;Ahmad;Mathematics,2022

2. Binary simulated normal distribution optimizer for feature selection: theory and application in COVID-19 datasets;Ahmed;Expert Syst. Appl.,2022

3. Enhancing machine learning prediction in cybersecurity using dynamic feature selector;Ahsan;J. Cybersecurity Privacy,2021

4. Artificial intelligence algorithm-based economic denial of sustainability attack detection systems: cloud computing environments;Aldhyani;Sensors,2022

5. Botnet attack detection using local global best bat algorithm for industrial internet of things;Alharbi;Electronics,2021

Cited by 1 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. A Machine Learning-Based Framework with Enhanced Feature Selection and Resampling for Improved Intrusion Detection;Mathematics;2024-06-09

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