Network security situation based on big data environment
Ye Yuan, Wenli Xu · 6th International Workshop on Advanced Algorithms and Control Engineering (IWAACE 2022) · 2022
In the big data environment, network security problems emerge in endlessly. If using traditional methods to predict the risk of the network security situation, network security situational awareness methods have the problems of inaccurate risk assessment and misjudgment of the risk level. Therefore, this paper proposes research on network security situations based on a big data environment. In the context of a big data environment, this paper constructs a network security situation assessment system and determines the membership degree of risk indicators according to the index assessment system. It also calculates the risk value of the security situation to clarify the risk level of network security situation, and to compare the security situation prediction method designed in this paper with the traditional prediction method through experimental demonstration. The results show that, compared with the traditional method, the results of the network security situation assessment of the prediction method designed in this paper are consistent with the actual security situation risk value of the network system. There is almost no error, which proves that the new method designed in this paper has higher prediction accuracy and is more efficient and reliable for the assessment of network security situation.