IoT Device Identification based on Network Traffic Analysis and Machine Learning
Stephanie M. Opoku, Habib Louafi, Malek Mouhoub · 2024
As Internet of Things (IoT) technology rapidly evolves, the widespread use and diversity of IoT devices present new challenges for device identification (often called finger-printing). Nevertheless, traditional methods for identifying IoT devices face several problems. This paper presents an identification solution capable of detecting the IoT device identities by analyzing the network traffic they generate and machine learning approaches. The solution we propose is tested on three well-known IoT traffic datasets, and showed higher prediction performance in identifying IoT device types. It is also compared against existing solutions and showed far better results, in terms of both prediction accuracy and temporal complexity.