Research on Hierarchical Network Security Situational Awareness Data Fusion Method in Big Data Environment

Abstract

Abstract With the globalization of information and the development of big data technology, people rely more and more on the network. The network brings convenience to everyone at the same time, and many security problems also come. This paper first introduces the NSSA model from different perspectives and analyzes the characteristics of its application, combined with the information fusion to put forward the H-NSSA system model, and constructs the framework of the network security posture assessment. Then, we assess the credibility of the intrusion behaviors in the network, classify and fuse the relevant evidence, and optimize the evidence conflict synthesis rules on this basis to improve the confidence of the event. The Bayesian network model is constructed by describing the causal relationship between elements using the assignment relationship model. Finally, experimental simulation and practical application analysis methods are used to study the network security situation and situation assessment, as well as the practical application of the actual situation in enterprises. The results show that the network suffered a large degree of attack in the 9th-12th time window and a medium degree of attack in the 42nd-43rd time window, and the H-NSSA algorithm model can reach asymptotic convergence in only 68 iterations, and the performance of the algorithm is high.