作者
Sinan Çalışır, Remzi Atay, Meltem Kurt Pehlivanoğlu, Nevcihan Duru
发表日期
2019/9/11
研讨会论文
2019 4th International Conference on Computer Science and Engineering (UBMK)
页码范围
656-660
出版商
IEEE
简介
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.
引用总数
20202021202220233543
学术搜索中的文章
S Çalışır, R Atay, MK Pehlivanoğlu, N Duru - 2019 4th International Conference on Computer …, 2019