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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) Jurnal Teknologi Informasi dan Komunikasi JTERA (Jurnal Teknologi Rekayasa) JOURNAL OF APPLIED INFORMATICS AND COMPUTING JURNAL REKAYASA TEKNOLOGI INFORMASI JMM (Jurnal Masyarakat Mandiri) JITTER (Jurnal Ilmiah Teknologi Informasi Terapan) ILKOM Jurnal Ilmiah METHODIKA: Jurnal Teknik Informatika dan Sistem Informasi EXPLORE Jurnal Mantik Jurnal Sistem Informasi dan Sains Teknologi Unram Journal of Community Service (UJCS) Journal of Computer Science and Informatics Engineering Prosiding Seminar Nasional Sisfotek (Sistem Informasi dan Teknologi Informasi) EXPLORE Jurnal Bangun Abdimas Jurnal Teknik Informatika dan Teknologi Informasi Formosa Journal of Computer and Information Science Jurnal Ilmiah Pengabdian dan Inovasi Jurnal Publikasi Teknik Informatika (JUPTI) Journal Of Computer Science And Technology Semar : Jurnal Sosial dan Pengabdian Masyarakat Jurnal Rekayasa Sistem Informasi dan Teknologi Jurnal Penelitian Teknologi Informasi dan Sains Journal of Computer Science and Information Technology Jurnal Kecerdasan Buatan dan Teknologi Informasi Journal of Data Analytics, Information, and Computer Science (JDAICS) Explore E-Amal: Jurnal Pengabdian Kepada Masyarakat Green Engineering: Journal of Engineering and Applied Science Journal of Information Technology and its Utilization Jurnal Teknik Informatika dan Teknologi Informasi Jurnal Karya untuk Masyarakat (JKuM)
Lalu Delsi Samsumar, M.Eng.
Universitas Teknologi Mataram
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Journal : JOURNAL OF APPLIED INFORMATICS AND COMPUTING

 1 
Anomaly-Based DDoS Detection Using Improved Deep Support Vector Data Description (Deep SVDD) and Multi-Model Ensemble Approach Imran, Bahtiar; Samsumar , Lalu Delsi; Subki, Ahmad; Wahyuni, Wenti Ayu; Muahidin, Zumratul; Karim, Muh Nasirudin; Yani, Ahmad; M. Zulpahmi
Journal of Applied Informatics and Computing Vol. 10 No. 1 (2026): February 2026
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v10i1.11863

Abstract

Distributed Denial-of-Service (DDoS) attacks remain a critical threat to network infrastructure, demanding robust and efficient detection mechanisms. This study proposes an enhanced Deep Support Vector Data Description (Deep SVDD) model for unsupervised DDoS detection using the UNSW-NB15 dataset. The approach leverages a deep encoder architecture with batch normalization and dropout to learn compact latent representations of normal traffic, minimizing the hypersphere volume enclosing benign flows. Only normal samples are used during training, adhering to the unsupervised anomaly detection paradigm. The model is evaluated against five established baselines—Isolation Forest, Local Outlier Factor (LOF), One-Class SVM, Autoencoder, and a simple ensemble—using AUC, F1-score, and recall as primary metrics. Experimental results demonstrate that Deep SVDD significantly outperforms all baselines, achieving superior class separation, high detection sensitivity, and computational efficiency (0.0004 GFLOPs). Notably, while LOF exhibited a deceptively high F1-score, its AUC near 0.5 revealed poor discriminative capability, highlighting the risk of relying on single metrics. The ensemble approach failed to improve performance, underscoring the limitation of naive score averaging when weak detectors are included. Visualization of score distributions and ROC curves further confirms Deep SVDD’s ability to effectively distinguish DDoS from benign traffic. These findings affirm that representation learning in latent space offers a more reliable foundation for anomaly detection than traditional distance-, density-, or reconstruction-based methods. The proposed model presents a promising solution for real-time, low-overhead intrusion detection systems in modern network environments. Future work will explore adaptive ensembles, self-supervised pretraining, and deployment on edge devices.
Co-Authors Ahmad Khairul Anam Ahmad Subki ahmad yani Aini Husnida Wulandari Akbar , Ardiyallah Akbar, Ardiyallah Amalia Rahman Amiruddin Kalbuadi Amirudin Kalbuadi Anindita Septirini Ardiyallah Akbar Ardiyallah Akbar Ardiyallah Akbar Aspari, Roni Astutik Zaerani Aulia, Asma Ayu Awanda Aerin Maesyarani Ayuni Azhuri Baiq Hanna Kurratul Aini Beni Ari Hidayatulloh Beni Ary Hidayatullah Beni Ary Hidayatullah Beni Iskandar Firdaus Lubis Biaq Widari Datu Samara Buchtami, Lalu Reza Dedi Supriadi Efendi, Muhamad Masjun Fadhillah Hasbi Ilyas Fadia Karunia Utami Fasya, Muhammad Rafli Feni Ayu Putri Fira Ria Sutardi Gunawati, Junita Haidar, Muhammad Zul Hambali Hambali Hambali Hambali Hamzan Wadi Ilyas, Fadhillah Hasbi Imran, Bahtiar Ismayani Jaelani, Lalu Rizki Juma’in, Juma’in Juniyardi, Lalu Kalbuadi, Amirudin Karim, Muh Nasirudin Karya Gunawan Kembang, Lale Puspita Kristy, Rhama Aziz Aulia Kusuma, Ali Pandu Laela Uziah Lalu Darmawan Bakti, Lalu Darmawan Lalu Isnaeni Rahman Lihana M. Budiamin M. Yusuf M. Zulpahmi M.Zulpahmi Mahmud Mahmud Misniati Misniati, Misniati Moh. Subli Moh. Subli Muahidin, Zumratul Muh. Nasirudin Muhamad Miskar Muhammad Nasirudin Karim Muhammad Rijal Alfian Mulyadi, M. Erwin Mutaqin, Zaenul Ni Wayan Adelia Mutiara Asri Novianti Puspitasari Panji Wijayanto Paripurna, Rian Bintang Puspita Kembang, Lale Puspitasari, Novianti Putri Novia Dyah Pitaloca ratih ratih Rian Bintang Paripurna Riandi Akbar Ramiz Rispawati, Dewi Rudi Muslim Sahida, Nirmala Said, Syukroni Salman Salman Salman Salman Sapitri, Nurul Saputra, Muliadi Sari, Ika Mayang Septirini, Anindita Silpa Rani Zain Sofian Hadi Sri Maryanti Sriasih, Sriasih Subki, Ahmad Sugeng Widodo Suja’i, Ahmad Supardianto Supardianto Suryadi, Emi Sutrisno, Sutrisno Tony Gunawan wahyuni, wenti ayu Wardani, Laila Wijaya, I Gusti Ngurah Satria Yumarlin MZ Zaenaldi, Firki Zaeniah Zaeniah Zaenudin Zaenudin Zaenudin Zaenudin Zaenudin Zaenudin Zaenudin Zaenudin Zaenudin Zaenudin Zaenudin Zaenudin Zaenudin Zaenudin Zaenul Mutaqin Zaenul Muttaqin Zenudin, Zaenudin Zulpahmi, M Zulpahmi, M.