Machine learning uses algorithms to turn a data set into a model that can identify patterns or make predictions from new data. Which algorithm works best depends on the problem.

In the model acquisition phase, extraneous features are used as input components for machine learning, and a random forest algorithm is used to model the model to detect the attacker. The test results ...