Design of Artificial Intelligence Aided Network Intrusion Detection System for Critical Infrastructure
Han Liu, Shuai Li, Dingding Li, Zheng Wang, Di Lun · 2025
An artificial intelligence (AI)-aided network intrusion detection system (IDS) for critical infrastructure is designed to cope with the increasingly severe network security threats. Once the critical infrastructure is invaded by network, it may lead to serious consequences such as service interruption and data leakage, which will affect national security and social stability. Traditional network IDS has some shortcomings in detection accuracy, false alarm rate and realtime performance, so it is difficult to meet high security requirements. Therefore, this study proposes a design scheme of IDS based on technology. The system adopts modular design, including data acquisition, preprocessing, feature extraction, AI intrusion detection and response processing modules. In the research of key technologies, the deep neural network (DNN) is chosen as the core algorithm, because it can effectively process large-scale high-dimensional data and automatically learn deep features. At the same time, feature selection and dimensionality reduction are used to optimize the feature extraction process and improve the detection efficiency. In the model training, the convolutional neural network (CNN) architecture is adopted, and the parameters are updated by Adam optimization algorithm to improve the model performance. The experimental evaluation uses KDD CUP 99 data set. After data cleaning, standardization and feature selection, the data set is divided into training set, verification set and test set. The experimental results show that CNN model has higher accuracy (92.3 %), recall (89.4 %) and F1 score ($\mathbf{9 0. 5 \%}$) in intrusion detection tasks, which is superior to traditional algorithms. This study is of great significance for improving the network security protection ability of key infrastructure, and also provides a new idea for the development of network security technology.