Kernekoncepter
This research paper proposes a novel deep learning model for detecting DDoS attacks that leverages a weighted ensemble of three CNN architectures enhanced with self-attention mechanisms and combined with XGBoost, LSTM, and Random Forest classifiers, demonstrating superior performance compared to traditional methods.
Kanthimathi, S., Venkatraman, S., S, J. K., T, P. J., & R, J. (2017). A Novel Self-Attention-Enabled Weighted Ensemble-Based Convolutional Neural Network Framework for Distributed Denial of Service Attack Classification. VOLUME XX, 2017, XX, 1–10. https://doi.org/10.1109/ACCESS.2022.Doi
This paper aims to improve the accuracy of DDoS attack detection by introducing a novel deep learning framework that addresses the limitations of traditional methods in effectively extracting diverse features from network traffic data.