Decision Tree Model-Based Security Situational Awareness Approach for Wireless Communication Networks

Network security situational awareness is gaining increasing attention due to its capability to globally and dynamically detect potential network security risks. However, traditional security situational awareness models often exhibit poor classification performance, resulting in lower-than-expected acceleration and scalability ratios. In this paper, we propose a novel security situational awareness approach for wireless communication networks based on a decision tree model. First, reconfigure the category division module to categorize the attack data into four different types. Then, using time windows to segment the data flow between the network and the host promotes the design of effective security event detection mechanisms in the model. Finally, a comprehensive network security situational awareness model was constructed at the joint level using decision tree algorithm. The experimental results show that the proposed method can significantly improve the acceleration ratio, and the space occupancy ratio can reach 80, indicating that the proposed method can have a high level of processing capability and accurate perception in network security situations, providing a guarantee for the security of wireless communication networks.