A Group-Based IoT Devices Classification Through Network Traffic Analysis Based on Machine Learning Approach
Avewe Bassene, Bamba Gueye · 2021
With the rapid growth of the Internet of Things (IoT), the deployment, management, and identification of IoT devices that are connected to networks become a big concern. Consequently, they emerge as a prominent challenge either for mobile network operators who try to offer cost-effective services tailored to IoT market, or for network administrators who aim to identify as well reduce costs processing and optimize traffic management of connected environments. In order to achieve high accuracy in terms of reliability, loss and response time, new devices real time discovery techniques based on traffic characteristics are mandatory in favor of the identification of IoT connected devices.