This project aims to identify and classify the anomalies captured in network traffic using different machine learning strategies. After the reults are given, I compared the results of two classical approaches for supervised learning: RandomForest and SVM on a large public combined dataset made from CICIDS2017 dataset and CICIDS2018.
