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DDOS Attack Detection Using Deep Learning by Ich Shoikot is a document available to read on EtoBox.
This paper presents a semi-supervised deep learning approach for detecting Distributed Denial of Service (DDoS) attacks, utilizing an improved autoencoder model with Gated Recurrent Units and an attention mechanism. The method leverages normal event data for training and employs local outlier factor algorithms for anomaly detection, achieving high accuracy and precision in identifying DDoS attacks. The results demonstrate the effectiveness of the proposed framework, particularly in handling unlabeled data,
- Author
- Ich Shoikot
- Language
- EN