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All Journal Indonesian Journal on Computing (Indo-JC) JITTER (Jurnal Ilmiah Teknologi Informasi Terapan) Competitive Merpati: Media Publikasi Pengabdian Kepada Masyarakat Politeknik Pos Indonesia Competitive
Mohamad Nurkamal Fauzan
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Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Mechanical Engineering Transportation

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Journal : Indonesian Journal on Computing (Indo-JC)

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QUIDS: A Novel Edge-Based Botnet Detection with Quantization for IoT Device Pairing Aji Gautama Putrada; Nur Alamsyah; Mohamad Nurkamal Fauzan; Sidik Prabowo; Ikke Dian Oktaviani
Indonesia Journal on Computing (Indo-JC) Vol. 8 No. 3 (2023): December 2023
Publisher : School of Computing, Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34818/INDOJC.2023.8.3.878

Abstract

Advanced machine learning has managed to detect IoT botnets. However, conflicts arise due to complex models and limited device resources. Our research aim is on a quantized intrusion detection system (QUIDS), an edge-based botnet detection for IoT device pairing. Using knearest neighbor (KNN) within QUIDS, we incorporate quantization, random sampling (RS), and feature selection (FS). Initially, we simulated a botnet attack, devised countermeasures via a sequence diagram, and then utilized a Kaggle botnet attack dataset. Our novel approach includes RS, FS, and 16-bit quantization, optimizing each step empirically. The test results show that employing a mean decrease in impurity (MDI) by FS reduces features from 115 to 30. Despite a slight accuracy drop in KNN due to RS, FS, and quantization sustain performance. Testing our model revealed 1200 RS samples as optimal, maintaining performance while reducing features. Quantization to 16-bit doesn’t alter feature value distribution. Implementing QUIDS increased the compression ratio (CR) to 175×, surpassing RS+FS threefold and RS by 13 times. This novel method emerges as the most efficient in CR.
Co-Authors Aji Gautama Putrada Ikke Dian Oktaviani Muhammad Adam Nahdlotul Halimi Noviana Riza NUR ALAMSYAH Roni Habibi Rony Andarsyah Sidik Prabowo Woro Istirahayu