A Study on Machine Learning Algorithms for IOT-Based Intrusion Detection System

In recent years, the need for IoT and its applications has grown and evolved significantly. However, as the number of attacks on IoT applications has expanded, so has the frequency of these attacks. This study intends to give a comprehensive assessment of recent research trends in IoT security, with a focus on identifying distinct security concerns in IoT and investigating the application of intrusion detection systems in IoT networks. Furthermore, the study investigates the incorporation of IoT security into machine learning (ML) security, which aids in the protection of machine learning models against various cyber-attacks. Furthermore, this study evaluates existing models and methods while highlighting several hybrid approaches for network analysis in intrusion detection. The accuracy and efficiency of the utilized approaches and models substantially influence the success of real-time IoT attack identification.