Aiming at the problems of the network security evaluation indexes, which are one-sided and difficult to be strictly quantified, this paper proposes the multidimensional system security evaluation method based on AHP and grey relational analysis. Under the guidance of the construction principle of system security evaluation model, this paper puts the source of factors affecting network security as the criterion of dimension Division, and constructs a multidimensional system security evaluation model for environmental security, network security and vulnerability security. On this basis, this paper combines AHP and grey relational analysis theory, and evaluate system security comprehensively and quantitatively. The multidimensional system security evaluation method based on AHP and grey relational analysis can consider the relationship between qualitative and quantitative factors in system security, and it is highly logical and flexible. This method also can effectively solve the problem that system security is difficult to evaluate objectively and quantitatively, and the system security evaluation can be pushed from a simple rough comparison to a comprehensive quantitative calculation stage.

Research on Multidimensional System Security Assessment Based on AHP and Gray Correlation

In recent years, with the rise of the global network, the Internet technology as the core of large enterprise network system is developing rapidly. It is widely used in the field of electronic commerce, information service, network communication and other technical means. At the same time, the problem of network security has become increasingly prominent. Due to historical and technical reasons, the security system of enterprise network is still very weak in China. The network basic software and hardware is still use a large number of foreign products, and the core of the network security technology cannot be fully mastered. So, the security risks are obvious. Therefore, strengthening the construction of enterprise network security system and researching the safe application model has become the top priority of our country's enterprise information technology. Based on this, we propose a smoothing method to improve the initial weights and the initial threshold, and use a test method to select the hidden layer node number of neural network. So, we can minimize the fitting error of the training. In this paper, the computer network security data of an enterprise is selected, and all the indexes are scored by the experts. The result of the scoring is the input value of the improved BP neural network. Finally, we use this algorithm to predict the network security of a certain enterprise in the next three months. The score is 0.85, 0.88 and 0.91, which is close to the actual value of network security.

Application of an Improved Bp Neural Network Model in Enterprise Network Security Forecasting

With the continuous expansion of the network scale in recent years, network security problems have become increasingly prominent, and network security incidents have emerged one after another. Network security situation awareness is an essential part of network security defense that allows cybersecurity operators to cope with the complexity of today’s networks and threat landscape. In this paper, we thoroughly review and systematize the origin and the models of network security situational awareness and the evolution of its definition, and then we give its definition. Additionally, we introduced the key technologies in this field from the three functional modules of network security situation extraction, network security situation assessment, and network security situation prediction, and analyzed their advantages and disadvantages. Last but not least, we explicitly propose four possible research directions that the researchers in network security can work on in the future.

Research Progress and Future Trend Analysis of Network Security Situational Awareness

In order to improve the assessment accuracy of network security situation,this paper put forward a network security situation assessment model based on grey relational analysis and support vector machineIt selected evaluation indexes accor-ding to the network security situation assessment rule accurately,and used grey relation analysis to determine the index weightThen it input the data to a support vector machine to train,which used the improved particle swarm optimization algorithm to optimize the parameters to establish the network security situation assessment modelFinally it carried out the simulation experi-ment by KDD Cup99 dataSimulation results show that the proposed model can assess network security situation accurately and objectively,and the assessment results can provide valuable advice for network administrator

Wang Cai-yin

Papers

Assessment of network security situation based on grey relational analysis and support vector machine