Research on DDoS detection method based on XGB-Trans

Min Sun; Ruodong Ren

doi:10.1117/12.2668053

20 April 2023 Research on DDoS detection method based on XGB-Trans

Min Sun, Ruodong Ren

Proceedings Volume 12602, International Conference on Electronic Information Engineering and Computer Science (EIECS 2022); 126021E (2023) https://doi.org/10.1117/12.2668053
Event: International Conference on Electronic Information Engineering and Computer Science (EIECS 2022), 2022, Changchun, China

Abstract

Aiming at the problems that current DDoS detection methods are difficult to capture long-distance time-series correlation between network traffic, low detection accuracy and insufficient ability to detect unknown types of DDoS attacks, a Transformer-based DDoS detection method XGB-Trans is proposed. First, the feature selection module based on the XGBoost is used to reduce the feature dimensionality of the data; then, the Transformer after the optimized architecture is used to extract the time-series related features between the low-dimensional data, and detect DDoS attacks accordingly. The experimental results on two network security datasets show that the detection accuracy and the generalization ability of the XGB-Trans are superior to other methods, and it has the ability to detect unknown DDoS attacks.

Citation Download Citation

Min Sun and Ruodong Ren "Research on DDoS detection method based on XGB-Trans", Proc. SPIE 12602, International Conference on Electronic Information Engineering and Computer Science (EIECS 2022), 126021E (20 April 2023); https://doi.org/10.1117/12.2668053

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