The computer network security situation awareness based on decision tree algorithm Online publication date: Sat, 18-May-2024
by Dehua Kong; Lin Lu; Nian Xiao
International Journal of Reasoning-based Intelligent Systems (IJRIS), Vol. 16, No. 2, 2024
Abstract: Aiming at the problems of security awareness error and high channel collision rate in computer network security awareness, a computer network security situation awareness method based on decision tree algorithm is proposed. First, the computer network architecture and security requirements are analysed. Then, the security situation index classification model is constructed, the network status data is collected, and the data features are extracted using the artificial fish swarm algorithm. Finally, the maximum information gain attribute is used as a sub node of the decision tree to generate a decision tree. Combined with cosine similarity, computer network security situational awareness is realised. The experimental results show that the correlation of the impact indicators of this method is higher than 0.5, the absolute percentage error of security situation awareness is lower than 0.5%, and the channel collision rate is 0~0.10 × 10-2.
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