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Intrusion Detection Using Machine Learning and Deep Learning Techniques
Calisir Sinan, Atay Remzi, Pehlivanoglu Kurt Meltem, Duru Nevcihan,
Published in
Pages: 656 - 660
Unlike traditional Denial of Service (DoS) attacks, application layer DoS attacks are nearly undetectable at the network layer. CIC DoS is one of the intrusion detection dataset which includes application layer DoS attacks. Therefore in this study, we handle this dataset to detect application based DoS attacks by using Random Forest, Extreme Gradient Boosting (XGBoost), Light Gradient Boosting Machine (LGBM), Gradient Boosting, Multilayer Perceptron (MLP), Convolutional Neural Networks (CNN) and Support Vector Machine (SVM) algorithms. The experimental results show that the performance of the LGBM based model is better than the other algorithms.
About the journal
JournalUBMK 2019 - Proceedings, 4th International Conference on Computer Science and Engineering
Open AccessNo