Remote Host Operation System Type Detection Based on Machine Learning Approach

Abstract

There are the research results of using machine learning to solve the problem of the remote host operating system detection in the article. The analysis of existing methods and means of detection of the remote host operating system are carried out, the main advantages and disadvantages of their using are defined. Modeling of machine learning methods is carried out. The software architecture is designed and experimental application is developed. It uses a trained machine learning model that allows detecting the type and version of operating system with high accuracy.