Novel classification of IoT devices based on traffic flow features

Abstract

The concept of IoT (internet of things) assumes a continuous increase in the number of devices, which raises the problem of classifying them for different purposes. Based on their semantic characteristics, meaning, functionality, or domain of usage, the system classes have been identified so far. This study's purpose is to identify device classes based on traffic flow characteristics such as the coefficient of variation of the received and sent data ratio. Such specified classes can combine devices based on behavior predictability and can serve as the basis for the creation of network management or network anomaly detection classification models. Four generic classes of IoT devices were defined using the classification of the coefficient of variation method.