Research on network intrusion detection based on SMOTEENN and improved CatBoost algorithm

Huoming Zhang; Yinhui Zhang; Pinglan Lu; Cheng Wang

doi:10.1117/12.3003918

11 October 2023 Research on network intrusion detection based on SMOTEENN and improved CatBoost algorithm

Huoming Zhang, Yinhui Zhang, Pinglan Lu, Cheng Wang

Proceedings Volume 12800, Sixth International Conference on Computer Information Science and Application Technology (CISAT 2023); 128001U (2023) https://doi.org/10.1117/12.3003918
Event: 6th International Conference on Computer Information Science and Application Technology (CISAT 2023), 2023, Hangzhou, China

Abstract

To address the problems of network intrusion data imbalance and prediction accuracy, a network intrusion detection model based on SMOTEENN (Synthetic Minority Oversampling Technique Edited Nearest Neighbor) and improved CatBoost algorithm is proposed, and SMOTEENN sampling is used to solve the data imbalance problem from the data level. The original CatBoost algorithm loss function is replaced with focal loss function to enhance the classification performance of CatBoost algorithm from the level of sample classification difficulty. And the Bayesian optimization algorithm is used to realize the CatBoost hyperparameter combination seeking. The network intrusion dataset NSL-KDD (National Security Letter Knowledge Discovery in Database) is input to the improved model and compared with other similar algorithms. The results show that the proposed method in this paper is optimal in terms of accuracy, F1-sacore, and AP value, To provide new ideas for network intrusion algorithm research.

(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Huoming Zhang, Yinhui Zhang, Pinglan Lu, and Cheng Wang "Research on network intrusion detection based on SMOTEENN and improved CatBoost algorithm", Proc. SPIE 12800, Sixth International Conference on Computer Information Science and Application Technology (CISAT 2023), 128001U (11 October 2023); https://doi.org/10.1117/12.3003918

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available