Network intrusion detection method based on GrC-CVM

Lijuan Cai; Yuhong Shi; Jiali Cai

doi:10.1117/12.3012266

21 December 2023 Network intrusion detection method based on GrC-CVM

Lijuan Cai, Yuhong Shi, Jiali Cai

Proceedings Volume 12970, Fourth International Conference on Signal Processing and Computer Science (SPCS 2023); 129703Q (2023) https://doi.org/10.1117/12.3012266
Event: Fourth International Conference on Signal Processing and Computer Science (SPCS 2023), 2023, Guilin, China

Abstract

Network intrusion detection is a research hotspot of network security technology. To solve this problem, a network intrusion detection algorithm based on GrC-CVM is proposed. Firstly, through the idea of hierarchical granulation of Granular computing (GrC), the attribute features of the sample are reduced, the minimum feature set is found, and redundant attributes are removed. Then, using the advantages of Core Vector Machine (CVM) in processing big data, the intrusion detection model is constructed by using the reduced feature set. Finally, the model is tested by using test set samples and compared with other relevant algorithms. The experimental results show that the algorithm can greatly improve the detection efficiency while ensuring the detection accuracy, and is superior to other algorithm models, and can be used as a network intrusion detection tool.

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

Citation Download Citation

Lijuan Cai, Yuhong Shi, and Jiali Cai "Network intrusion detection method based on GrC-CVM", Proc. SPIE 12970, Fourth International Conference on Signal Processing and Computer Science (SPCS 2023), 129703Q (21 December 2023); https://doi.org/10.1117/12.3012266

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