Proceedings of the 2023 9th International Conference on Humanities and Social Science Research (ICHSSR 2023)

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Intrusion Detection Model Based on Weighted Extreme Learning Machine

Authors
Chen Chen1, 2, Gang Wei2, *, Fan Qiang3, Dejiang Wan4, Guangyu Chen1
1State Key Laboratory of Astronautic Dynamics, Xi’an, China
2College of Air and Missile Defense, Air Force Engineering University, Xi’an, China
3Xichang Satellite Launch Center, Xichang, China
4Military Representative Bureau of Space System Equipment Department, Beijing, China
*Corresponding author. Email: wei_gang@163.com
Corresponding Author
Gang Wei
Available Online 9 September 2023.
DOI
10.2991/978-2-38476-092-3_139How to use a DOI?
Keywords
intrusion detection; weighted extreme learning machine; imbalanced dataset; hyperparameters selection
Abstract

An intrusion detection model based on weighted extreme learning machine (WELM) is proposed. By using the advantages of short training time and good generalization performance of WELM, the imbalance phenomenon in NSL-KDD intrusion detection dataset is increased, and the detection rate of rare attacks in network attacks is greatly improved compared with traditional machine learning methods, thus realizing the classification of NSL-KDD intrusion detection dataset. Experiments show that the precision and recall of this model for rare attacks are improved.

Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the 2023 9th International Conference on Humanities and Social Science Research (ICHSSR 2023)
Series
Advances in Social Science, Education and Humanities Research
Publication Date
9 September 2023
ISBN
10.2991/978-2-38476-092-3_139
ISSN
2352-5398
DOI
10.2991/978-2-38476-092-3_139How to use a DOI?
Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - Chen Chen
AU  - Gang Wei
AU  - Fan Qiang
AU  - Dejiang Wan
AU  - Guangyu Chen
PY  - 2023
DA  - 2023/09/09
TI  - Intrusion Detection Model Based on Weighted Extreme Learning Machine
BT  - Proceedings of the 2023 9th International Conference on Humanities and Social Science Research (ICHSSR 2023)
PB  - Atlantis Press
SP  - 1115
EP  - 1120
SN  - 2352-5398
UR  - https://doi.org/10.2991/978-2-38476-092-3_139
DO  - 10.2991/978-2-38476-092-3_139
ID  - Chen2023
ER  -