Research on feature classification of network intrusion detection based on deep learning

Feng Wei; Dongqing Liu; Ajun Cui; Lei Zhang

doi:10.1117/12.3052224

15 January 2025 Research on feature classification of network intrusion detection based on deep learning

Feng Wei, Dongqing Liu, Ajun Cui, Lei Zhang

Author Affiliations +

Proceedings Volume 13516, Fourth International Conference on Network Communication and Information Security (ICNCIS 2024); 135160S (2025) https://doi.org/10.1117/12.3052224
Event: International Conference on Network Communication and Information Security (ICNCIS 2024), 2024, Hangzhou, China

Abstract

To address the complexity of classifying network attack big data, the high dependency on prior knowledge, and the need to improve algorithm classification performance, this paper proposes a deep learning network based on CNN for classifying and detecting network attacks in network security situation awareness. A network feature transfer learning method is introduced to solve the detection and training efficiency problems of the CNN algorithm for complex data features in a big data environment. By optimizing the performance of the CNN algorithm, similarity distance is applied to solve the issue of low classification accuracy caused by data category imbalance, thus improving the efficiency and accuracy of algorithm classification calculations. Extensive simulation experiments were conducted to detect abnormal features of network attacks, and the improved CNN model was compared with the latest deep learning algorithms to verify the model's performance and target detection efficiency. The research provides a new idea for using deep learning methods to detect intrusion attacks in the context of complex network data.

(2025) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Feng Wei, Dongqing Liu, Ajun Cui, and Lei Zhang "Research on feature classification of network intrusion detection based on deep learning", Proc. SPIE 13516, Fourth International Conference on Network Communication and Information Security (ICNCIS 2024), 135160S (15 January 2025); https://doi.org/10.1117/12.3052224

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