Computer Network Security under the Background of Big Data

Abstract

With the advent of the era of big data, data has exploded. This paper mainly studies the analysis of computer network security under the background of big data. In order to make these data intuitively reflect the network security situation, this paper uses the method of weight allocation to normalize the five groups of data, and allocates a larger weight to the security problems with high network security threat and a small weight to the security problems with low network security threat. In this paper, 3603 sample data are randomly selected as evaluation data according to the proportion of the type of data set unchanged. After setting the parameters, you can train and test. According to the risk level, take corresponding control measures to control the system risk at an acceptable level. The data shows that a certain number of attacks are carried out on the protected network in the 5th, 12th, 20th, 28th, 36th, 44th and 52nd minutes, and the scale of each attack is twice that of the last attack. The results show that the construction and deduction method of network security event scenarios can provide effective support for the research of network security incident coping strategies.