ML-Driven Lightweight Botnet Detection System for IoT-Networks

Ashfaq Hussain Farooqi; Rizwan Ahmad; Shaharyar Kamal

Authors

Ashfaq Hussain Farooqi Department of Computer Science, Air University Islamabad, Pakistan https://orcid.org/0000-0002-4540-8697
Rizwan Ahmad Department of Computer Science, Air University Islamabad, Pakistan
Shaharyar Kamal Department of Electrical Engineering, University of Chile, Santiago, Chile

Keywords:

Internet of Things (IoT), Intrusion Detection System (IDS), Machine Learning (ML), Feature Selection Algorithm, Botnet Detection.

Abstract

The integration of cloud computing with the Internet of Things (IoT) seeks to create seamless connections between humans and devices, enhancing applications in areas like smart healthcare and home automation. However, this also brings significant security challenges. Our study addresses the critical need for an efficient anomaly detection system specifically designed for IoT-enabled cloud computing environments, a gap not previously explored at this scale. Utilizing the IoT-23 dataset, we evaluated various feature selection techniques in conjunction with classification algorithms to develop a lightweight anomaly detection model. Our results demonstrate that the decision tree classifier, paired with the correlation coefficient method for feature selection, achieved an impressive 99.98% accuracy rate, with an average processing time of just 5.2 seconds. This combination proved to be the most effective for real-time anomaly detection, presenting a promising approach for ensuring robust security in IoT networks as connectivity continues to grow.

Author Biography

Ashfaq Hussain Farooqi, Department of Computer Science, Air University Islamabad, Pakistan

Dr. Ashfaq Hussain Farooqi is currently working as Assistant Professor at the Department of Computer Science, Air University, Islamabad, Pakistan since Feb 2022. He completed his Ph.D. in Computer Science under the Indigenous Ph.D. Fellowship Program - Higher Education Commission (HEC) Pakistan from the National University of Computer and Emerging Sciences, Islamabad, Pakistan in 2018. He participated in the Japan-East Asia Network of Exchange for Students and Youths program held in Japan in 2010. He availed the IRSIP-HEC scholarship for the research fellowship and worked at Ubiquitous Computing Lab, Kyung Hee University, South Korea in 2011. He served as a Lecturer at the Department of Computer Science at the COMSATS University Islamabad, Pakistan from Dec 2012 till Feb 2022. He has reviewed and authored several articles in refereed international conferences and journals. His research interest includes wireless communication, network security, machine learning, blockchain, and artificial intelligence.

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