Exploring Machine Learning Methods for IoT Network Intrusion Detection Systems

Abstract

An ad hoc network is a transient network that is self-organizing and does not require any infrastructure. Therefore, the majority of its applications are in the field of military work and disaster assistance. Because of wireless connectivity and the ability to organize itself, ad hoc networks are becoming more common. Susceptible to a greater number of breaches or assaults than the conventional system. Blackhole assault is a significant routing disruption attack that a rogue node promotes itself as being capable of. as a step along the way to the final destination. In this research, we simulated a black hole using computer models. Assault in a setting with ad hoc networking, as well as data collection of important features for the purpose of classifying aggressive behaviour. Then, several different approaches to machine learning have been developed. utilized for the classification of information regarding benign and harmful packets. It seems to imply. a novel method for the selection of certain features, the gathering of crucial information, and the intrusion detection in an ad hoc network with the application of machine learning algorithms.