Research on industrial internet intrusion detection model based on optimized BI-GRU

Wenqiang Shi; Hao Wang; Yuanlin Gong; Hao Xu

doi:10.1117/12.2673890

6 April 2023 Research on industrial internet intrusion detection model based on optimized BI-GRU

Wenqiang Shi, Hao Wang, Yuanlin Gong, Hao Xu

Proceedings Volume 12615, International Conference on Signal Processing and Communication Technology (SPCT 2022); 126151Y (2023) https://doi.org/10.1117/12.2673890
Event: International Conference on Signal Processing and Communication Technology (SPCT 2022), 2022, Harbin, China

Abstract

The intrusion detection model based on deep learning has become a research hotspot in the field of network security, aiming at the high FPR and low DR of current intrusion detection systems, this paper proposes an anomaly detection model based on deep learning. The system is first optimized by particle swarm optimization. Data feature extraction, and then through the fusion of MLP's bidirectional GRU model to better mine the information contained in the data set and its correlation, and improve the efficiency and quality of feature extraction. Finally, experiments show that the model has good performance, with a detection readiness rate of 98.74%, a false positive rate of 0.029, and a detection rate of 98.42%. The results show that the detection effect of PSO+BI-GRU+MLP is better than other algorithm models.

Citation Download Citation

Wenqiang Shi, Hao Wang, Yuanlin Gong, and Hao Xu "Research on industrial internet intrusion detection model based on optimized BI-GRU", Proc. SPIE 12615, International Conference on Signal Processing and Communication Technology (SPCT 2022), 126151Y (6 April 2023); https://doi.org/10.1117/12.2673890

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