Anomaly detection of denial-of-service network traffic attacks using autoencoders and isolation forest

This paper presents an unsupervised network-based anomaly detection framework that integrates deep autoencoders with the Isolation Forest algorithm. The framework analyzes extracted traffic features, including packet length and IP address patterns, to detect deviations from normal behaviour without...

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Bibliographic Details

Main Authors:	Ghulam Hussain, Muhammad Thaqif, Shafeeq Lone, Aman, Maspo, Nur-Adib, Attarbashi, Zainab
Format:	Article
Language:	en
Published:	IIUM Press 2026
Subjects:	QA75 Electronic computers. Computer science QA76 Computer software TK7885 Computer engineering
Online Access:	http://irep.iium.edu.my/127399/7/127399_Anomaly%20detection%20of%20denial-of-service%20network.pdf http://irep.iium.edu.my/127399/ https://journals.iium.edu.my/kict/index.php/IJPCC/article/view/680
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