Abstract: In order to improve the prediction ability of network security level, a design method of network security level prediction system based on time window parameter identification and spatial interval sampling is proposed. According to the prediction feature of network security level, the browsing information and intrusion information feature of network users are detected, the distribution set of network intrusion and attack behavior characteristics reflecting network security level is constructed, the statistical feature quantity of network security level prediction is extracted, and the distributed feature extraction and adaptive detection of network intrusion are carried out according to the combined feature distribution of the network security level prediction network behavior feature set. The feature set and similarity attribute of network spatial distribution information of the load network security level are mined and combined with the estimation results of time parameters, the security level evaluation and optimization prediction are carried out, and the network intrusion optimization detection and security early warning are realized. The simulation results show that the method has strong response ability to predict the network security level, and the accurate detection performance of the network intrusion is better, which improves the prediction ability of the network security level and ensures the network security.

Key words: time parameter, network security, grade prediction, intrusion detection