Implementation of Multi-Layer Security Network Identification System Using Machine Learning Techniques

Abstract

The distinct parts of a multilayered security network have been designed in such a manner that the susceptibility of a single layer does not impact the additional layers, and therefore the entire network is not susceptible. As this paper provides a multiple-layer protected Internet of Things (IoTs) platform idea depending on machine learning (ML), this research will detail the creation of a multilayer security network system for authentication using ML. Employing a fuzzy inference structure, this work created a multi-layer random forest system for intrusion detection. In this study, the advantages of the filtering and wrapping methods are merged to develop an increasingly sophisticated multi-layer selecting features methodology that improves system security.