Research on Network Security Technology Based on Machine Learning
Fei Han · 2023
In recent years, with the popularization of the Internet, the network has penetrated into all aspects of individuals and society. Internet technology has made people's daily lives more intelligent and convenient, but the accompanying network security issues cannot be ignored. Network vulnerabilities and illegal intrusions can affect internet security, and even affect the construction of national infrastructure, critical defense systems, and even military systems. This article selects 50000 sets of data from the KDD99 cybersecurity dataset provided by the National Security Administration of the United States. Each sample in the dataset includes 41 feature attributes and 1 decision attribute. We constructed a model based on the random forest algorithm, using 30% of the total sample data as the test set and the remaining 70% of the data as the training set. Then, 100 sets of data were taken for model training. After the training was completed, the detection model successfully predicted 98 intrusions out of 100 detections, and the final score of the test set was 0.982, basically achieving the effect of intrusion detection. A machine learning algorithm model is provided for detecting network intrusions.