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This process receives input from network traffic records with two features, namely the Label feature as the target and the extracted features using dimensional reduction techniques. The classification is performed using machine learning algorithms Decision tree, Random forest, Logistic regression, Naive bayes, and k nearest neighbor. This process begins with data splitting, to divide the data into training as much as 80% of the total data and data testing, which uses all input data. The training results in the form of learning models are used in the classification process with several algorithms. The output of this process is a collection of normal and botnet activities |
IEEE/ICACT20230225 Slide.15
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