Design of Industrial IoT Intrusion Security Detection System Based on LightGBM Feature Algorithm and Multi-layer Perception Network
DOI:
https://doi.org/10.13052/jcsm2245-1439.1327Keywords:
LightGBM, multi-layer perception network, industrial IoT, intrusion detection, feature selectionAbstract
Continuous improvement of machine learning technology has provided more support for intrusion security detection in the industrial Internet of Things (IoT). The intrusion security detection system based on LightGBM feature algorithm and multi-layer perception network fusion provides more options for improving security detection, further enhancing the effectiveness of industrial IoT intrusion security detection. By comparing the applications of different models in the security detection process, the model constructed based on the LightGBM feature algorithm can achieve higher accuracy and precision in industrial IoT intrusion security detection, as well as higher F1-score and AUC values; A more reasonable detection time also lays the foundation for improving the overall efficiency of industrial IoT intrusion security detection. Therefore, in the field of industrial IoT intrusion security detection, the detection model constructed in this article can provide more support for further improvement and improvement of IoT intrusion security detection performance.
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