Information Security Situation Awareness Based on Big Data and Artificial Intelligence Technology

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.