Network intrusion detection method based on random forest

The invention discloses a network intrusion detection method based on a random forest. The method comprises the following four steps: S1, data preprocessing: enabling a network flow test data set to be subjected to normalization processing and uploading to a database; S2, data rebalancing: rebalancing the preprocessed data, and adding minority class samples; S3, binary classification model training: sending the data after data rebalancing into a random forest model for training to obtain a network intrusion detection model; S4, network intrusion determination: performing network intrusion determination on the test data through the model. According to the network intrusion detection method based on the random forest provided by the invention, the network intrusion can be trained through the network flow test data set, whether the network intrusion is an intrusion behavior is predicted, the network security intelligent detection process is realized, and the network risk prevention and control capability is effe