Abstract
The information security threats faced by enterprises are increasing rapidly, and the technology of security attacks is also diversified and developed at a high level. The application of big data technology and artificial intelligence technology in all walks of life continues to deepen. While greatly improving social productivity, it also brings certain information security issues. Security situation awareness technology has become a new research hotspot in the field of network security. Using big data-related technologies to analyze, filter, merge, and identify known and unknown security threats is a new research discovery. This research builds a new cascaded network security situational awareness model based on the traditional and fusion decision tree algorithms. We use an induction algorithm to generate a decision tree on the preprocessed data to classify the data according to the decision rules. Research shows that a new network security situation awareness model is constructed using decision tree calculations. Compared with the traditional model, the classification effect of this model is better.
Highlights
The rapid development of cloud computing and the Internet has caused an explosive growth of network data
The security situation awareness technology is designed, such as the network security situation awareness model based on the Bayesian method and the multinode network security situation prediction awareness model based on the improved G-K algorithm
This research builds a new cascaded network security situational awareness model based on the traditional model fusion decision tree algorithm
Summary
The rapid development of cloud computing and the Internet has caused an explosive growth of network data. The security situation awareness technology is designed, such as the network security situation awareness model based on the Bayesian method and the multinode network security situation prediction awareness model based on the improved G-K algorithm These two models detect security events in the network by sensing network security threat data, but the classification effect of the security situation awareness model is not good [1]. This has led to its speedup and scale ratios being lower than expected. The design process of the cascaded network security situational awareness model based on the decision tree algorithm is described in detail below
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