Network Intrusion Detection Model Based on Artificial Intelligence
Qingchuan Meng, Youzi Zhang, Fengzhi Wu, Xiaoming Chen · Journal of Physics Conference Series · 2020
Abstract The Internet occupies a more and more important position in people’s life. The society has become more convenient because of the progress of network technology, and the network security problem has attracted more and more attention. Therefore, the security technology based on network is more and more important. Intrusion detection technology is the main research direction of dynamic security tools. Aiming at the problem of low accuracy of network intrusion detection, this paper proposes a network intrusion detection model based on AI, introduces artificial intelligence neural network and algorithm, extracts data feature information through repeated training of the algorithm, and constructs network intrusion monitoring model based on neural network. According to the design goal of the model, the basic framework of the system is given, which provides accurate detection basis for network intrusion detection. The experimental results show that the detection accuracy of the model is high.