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Hybrid CNN-XGBoost for DDoS Detection by yash.caml.13 is a document available to read on EtoBox.

This paper presents a hybrid model combining Convolutional Neural Networks (CNN) and Extreme Gradient Boosting (XGBoost) for detecting DDoS and DoS attacks in network traffic, achieving an accuracy of 99.68%. The model utilizes advanced preprocessing techniques and feature selection from the NF-UQ-NIDS-v2 dataset, demonstrating superior performance compared to traditional methods. The proposed approach effectively integrates deep learning for feature extraction with robust classification, offering a scalabl

Author

yash.caml.13

Language

EN