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And This is the architecture of our proposed method. We used three bidirectional network flow botnet dataset, namely: scenario 9 from CTU-13, scenario 9 NCC-1, and sensor 3 from NCC-2. Then, pre processing phase, start with data cleansing, followed by data transformation, and feature selection. Next phase is feature extraction with several dimentional reduction technique, namely: SVD, PCA, F A and Fast I C A. In order to evaluate the dimentional reduction technique, we do some approach like unique value selection, and sampling, before measure the similarity of botnet and normal data. This proposed method use several classification algorithm, Random forest, KNN, Decision tree, logistic regression and naive bayes to get the classification result |
IEEE/ICACT20230225 Slide.12
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