Design And Implementation Of Network Security Situation Awareness System Based On Neural Network

With the development of network technology,the scale and complexity of the network are increasing,the network has more and more loopholes,the network attack technology is constantly innovating,and new types of attacks are emerging.The traditional network security technology has been unable to defend the attack.In this case,cybersecurity situational awareness technology emerged.Network security situational awareness mainly collects situational information related to network security in the system through various sensing devices,comprehensively assesses the current running status of the network as a whole and predicts the development trend of future network conditions,helping network managers to quickly make React,reduce or avoid loss.Network security situational awareness technology is currently receiving a lot of attention and has become a hot research topic in recent years.This paper designs and implements a complete network security situational awareness prototype system,from basic data collection to situation assessment,and then through situation prediction,and finally presents various information to users intuitively and clearly.The main work of this paper is as follows:1.The situational awareness classic model and situation assessment technology are studied,and a relatively complete security situation index system and a hierarchical evaluation model are constructed.The operation state of the network node,the vulnerability scan result and the network attack situation are three.The side describes the network security situation,and uses the combination of fuzzy comprehensive evaluation and analytic hierarchy process to quantify the situation indicators.2.The situation prediction technology is studied.In order to solve the shortcomings of the traditional RBF neural network training method,such as difficulty in initial center selection and easy to fall into local optimum,the cuckoo search algorithm is introduced into the training of RBF neural network,and a CS-based The state potential measurement method of RBF neural network,the structure and parameters of the network are designed in detail,the detailed prediction process is given,and then the experimental test is carried out.Compared with various other models,the CS-RBF neural network prediction method is verified.The superiority.3.Based on the research of situation assessment technology and situation prediction technology,the whole situational awareness system is designed and implemented.The demand analysis of the system is carried out,and the overall design of the system is given.The whole system is divided into data acquisition module,situation assessment module,situation prediction module,central management module and user interface,and the interaction process between each module is given.And then,detailed design and implementation of each module.