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All Journal International Journal of Electrical and Computer Engineering Jurnal Ilmu Komputer Jurnal Edukasi dan Penelitian Informatika (JEPIN) JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control ILKOM Jurnal Ilmiah INTEK: Informatika dan Teknologi Informasi Jurnal Abdimas PHB : Jurnal Pengabdian Masyarakat Progresif Humanis Brainstorming Applied Technology and Computing Science Journal Infotekmesin Jurnal Sistem informasi dan informatika (SIMIKA) Journal of Innovation Information Technology and Application (JINITA) Madani : Indonesian Journal of Civil Society Journal of Informatics, Information System, Software Engineering and Applications (INISTA) Media Aplikom Jurnal Pengabdian Teknologi Tepat Guna Jurnal Nasional Teknik Elektro dan Teknologi Informasi
Muhammad Nur Faiz
Politeknik Negeri Cilacap
Religion Humanities Automotive Engineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Energy Engineering Languange, Linguistic, Communication & Media Library & Information Science Mechanical Engineering Public Health Social Sciences Other

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Journal : Jurnal Nasional Teknik Elektro dan Teknologi Informasi

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Rekayasa Fitur Berbasis Machine Learning untuk Mendeteksi Serangan DDoS Muhammad Nur Faiz; Oman Somantri; Arif Wirawan Muhammad
Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 11 No 3: Agustus 2022
Publisher : Departemen Teknik Elektro dan Teknologi Informasi, Fakultas Teknik, Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/jnteti.v11i3.3423

Abstract

Distributed network attacks, also known as distributed denial of service (DDoS) are a major threat and problem for internet security. DDoS is an attack on a network aiming to disable server resources. These attacks increase every year with the current state of the COVID-19 pandemic. One of countermeasures to minimize the DDoS impact is the intrusion detection system (IDS) command. IDS techniques are currently still employing traditional methods so that they have many limitations compared to techniques and tools used by attackers because traditional IDS methods only use signature-based detection or anomaly-based detection models which cause many errors. Network data packet traffic has a complex nature, both in terms of sizes and sources. This research utilized the ability of artificial neural network (ANN) to detect normal attacks or DDoS. A classification technique with ANN method is a solution to these issues. Based on the shortcomings of the traditional IDS, this study aims to detect DDoS attacks using feeder machine learning-based feature engineering techniques to improve the IDS development. Using the UNSW-NB15 dataset with the ANN method, this study also aims to analyze and obtain training function combinations and the best hidden layer architectures of ANNs to solve the detection and classification problems of DDoS packets in computer networks. As a result, the training function combinations and hidden layer architectures of the ANN can provide a high level of DDoS recognition accuracy. Based on experiments conducted with three schemes and an ANN schema architecture technique with eight features as input, the highest accuracy was 98.22%. Feature selection plays an essential role in detection result accuracies and machine learning performances in classification problems.
Co-Authors Abdul Fadlil Abdul Rohman Supriyono Achmad Zaki Yamani Agus Susanto Agus Susanto Anggita Dwi Fatimah Annas Setiawan Prabowo Anton Yudhana Ari Kristiningsih Arif Wirawan Muhammad Davito Rasendriya Rizqullah Putra Dwi Cita Septia Candra Erna Alimudin Ganjar Ndaru Ikhtiagung Gautama Wijaya Haeruddin Hani Hidayati Hani Hidayati Hendra Winata Hety Dwi Astuti Ifda Nurul Azroha Imam Riadi Isa Bahroni, Isa Khoeruddin Wittriansyah Laura Sari Linda Perdana Wanti Linda Perdana Wanti Lutfi Syafirullah Lutfi Syarifullah Nur Chasanah Nur Wachid Adi Prasetya Nur Wahyu Rahadi Oman Somantri Prih Diantono Abda`u Ratih Hafsarah Maharrani Rusydi Umar Santi Purwaningrum Santi Purwaningrum Seppy Ayu Rachmawati Sidiq, Muhammad Fajar Sukma Aji Ummi Athiyah Wahyu Adi Prabowo