Botnet Detection in Internet of Things Devices: A Step Up with Intrusion Detection Systems

Hossain Pabel, Mohammad Shahadat (2024) Botnet Detection in Internet of Things Devices: A Step Up with Intrusion Detection Systems. Masters thesis, Dublin, National College of Ireland.

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Abstract

The exponential growth and popularity of the Internet of Things (IoT) have posed serious security risks, particularly the hazards of botnets. This research aims at filling the existing gap in effective feature engineering procedures for improving IoT botnet detection. In this project, we plan to use machine learning and deep learning to analyse a large-scale, real-time detection system that includes several data providing mechanisms. Our strategy involves feature extraction of high-level features, reducing the dimensionality of the problem, and the use of anomaly detection techniques. The results show enhanced performance and effectiveness in identifying botnet threats and offers a complete understanding of the IoT security.

Item Type:	Thesis (Masters)
Supervisors:	Name Email Aleburu, Joel UNSPECIFIED
Subjects:	Q Science > QA Mathematics > Electronic computers. Computer science T Technology > T Technology (General) > Information Technology > Electronic computers. Computer science Q Science > QA Mathematics > Computer software > Computer Security T Technology > T Technology (General) > Information Technology > Computer software > Computer Security T Technology > TK Electrical engineering. Electronics. Nuclear engineering > Telecommunications > Computer networks > Internet of things
Divisions:	School of Computing > Master of Science in Cyber Security
Depositing User:	Ciara O'Brien
Date Deposited:	17 Jul 2025 16:16
Last Modified:	17 Jul 2025 16:16
URI:	https://norma.ncirl.ie/id/eprint/8175

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