Research on hybrid intrusion detection based on improved Harris Hawk optimization algorithm-Reference-Cited by-同舟云学术

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Research on hybrid intrusion detection based on improved Harris Hawk optimization algorithm

Published:2023-04-19 Issue:1 Volume:35 Page:
ISSN:0954-0091
Container-title:Connection Science
language:en
Short-container-title:Connection Science

Author:

Zhou Pengzhen¹²,Zhang Huifu¹²,Liang Wei¹²

Affiliation:

1. College of Computer Sciences and Engineering, Hunan University of Science and Technology, Xiangtan, Hunan, People's Republic of China

2. Hunan Key Laboratory for Service Computing and Novel Software Technology, Xiangtan, Hunan, People's Republic of China

Funder

National Natural Science Foundation of China

Publisher

Informa UK Limited

Subject

Artificial Intelligence,Human-Computer Interaction,Software

Link

https://www.tandfonline.com/doi/pdf/10.1080/09540091.2023.2195595

Reference49 articles.

1. A feature selection algorithm for intrusion detection system based on Pigeon Inspired Optimizer

2. Multi-level hybrid support vector machine and extreme learning machine based on modified K-means for intrusion detection system

3. A Modified Grey Wolf Optimization Algorithm for an Intrusion Detection System

Cited by 5 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. Network intrusion classification for IoT networks using an extreme learning machine;Engineering Research Express;2024-05-28

2. Performance Evaluation of Whale and Harris Hawks Optimization Algorithms with Intrusion Prevention Systems;Lecture Notes in Networks and Systems;2024

3. Enhancing Network Intrusion Detection Systems Through Dimensionality Reduction;Lecture Notes in Networks and Systems;2024

4. A Modified Feature Selection Algorithm for Intrusion Detection System Based on Student Psychology-Based Optimization with Explainable AI;2023 IEEE Asia-Pacific Conference on Computer Science and Data Engineering (CSDE);2023-12-04

5. Feature Engineering and Model Optimization Based Classification Method for Network Intrusion Detection;Applied Sciences;2023-08-18

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