Machine Learning Theory and Practice, 2020, 1(2); doi: 10.38007/ML.2020.010203.
Yupeng Sang
College of Information and Technology, Wenzhou Business College, Wenzhou 325035, China
With the development of the network, the attack methods have become diverse. Malicious attackers can steal users' personal information by mining information. Therefore, this paper intends to study the role of decision tree algorithm in malicious network attacks and intrusions. The purpose is to improve the detection and defense of network attacks through this algorithm to ensure the information security of users. This paper mainly uses the method of experimental comparison and experimental construction to deeply explore the application of decision tree algorithm and PCA feature extraction in the system. The experimental results show that the intrusion accuracy based on decision tree algorithm can reach more than 90%, and the accuracy of PCA feature extraction can increase by 3%.
Decision Tree Algorithm, Malicious Network, Network Attack, Network Intrusion
Yupeng Sang. Malicious Network Attack and Intrusion Based on Decision Tree Algorithm. Machine Learning Theory and Practice (2020), Vol. 1, Issue 2: 19-27. https://doi.org/10.38007/ML.2020.010203.
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