Integration of machine learning algorithms for intrusion detection in IoT networks

Abstract

The study subject is detection systems for intrusions into IoT infrastructure and compromised IoT devices based on machine learning algorithms. The study object is a machine learning model that will detect anomalies in an IoT network's behaviour and identify patterns that indicate normal behaviour and deviations that may signal an intrusion. The study aims to enhance the security of IoT networks by developing effective and efficient intrusion detection systems using machine learning techniques. The authors offer an analysis tailored for security professionals, focusing on utilising machine learning techniques to develop a honeypot for detecting intrusions.