Network Security Situation Awareness Based on the Optimized Dynamic Wavelet Neural Network

In order to analyze the evolvement trend of the network threat and to explore the self-perception and control problem of the security situation, the dynamic wavelet neural network model is integrated into the model design, and a kind of network security situation awareness based on the optimized dynamic wavelet neural network is put forward, so as to enhance the interaction and cognitive ability between the layers of the network security system. On the basis of the analysis of the model components and their functions, the dynamic wavelet neural network algorithm is applied to obtain the accurate decision of the heterogeneous sensors for the network security events. Combined with the deduction of the relationship between the threat grade and threat genes, the shortcoming of the necessity to handle the complicated relationships among network components during the process to obtain the threat genes is overcome, and the hierarchical situation awareness method including the service level and network level is proposed to improve the expressiveness for the network threats. The simulation results show that: The network security situation awareness and method based on the optimized dynamic wavelet neural network can integrate the heterogeneous security data with dynamic perception on the evolution trend of the threat, and have the ability of self-regulation and control to certain extent, which has achieved the goal of situation awareness, and provided new methods and means for the supervision and management of network.