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Classification Of Ddos Attack With Machine Learning Architectures And Exploratory Analysis, Amreen Anbar
Classification Of Ddos Attack With Machine Learning Architectures And Exploratory Analysis, Amreen Anbar
Electronic Thesis and Dissertation Repository
The ever-increasing frequency of occurrence and sophistication of DDoS attacks pose a serious threat to network security. Accurate classification of DDoS attacks with efficiency is crucial in order to develop effective defense mechanisms. In this thesis, we propose a novel approach for DDoS classification using the CatBoost algorithm, on CICDDoS2019, a benchmark dataset containing 12 variations of DDoS attacks and legitimate traffic using real-world traffic traces. With a developed ensemble feature selection method and feature engineering, our model proves to be a good fit for DDoS attack type prediction. Our experimental results demonstrate that our proposed approach achieves high classification …