ScaNeF-IoT: Scalable Network Fingerprinting for IoT Device
Tadani Alyahya, Leonardo Aniello, Vladimiro Sassone · 2024
Recognising IoT devices through network fingerprinting contributes to enhancing the security of IoT networks and supporting forensic activities. Machine learning techniques have been extensively utilised in the literature to optimise IoT fingerprinting accuracy. Given the rapid proliferation of new IoT devices, a current challenge in this field is around how to make IoT fingerprinting scalable, which involves efficiently updating the used machine learning model to enable the recognition of new IoT devices. Some approaches have been proposed to achieve scalability, but they all suffer from limitations like large memory requirements to store training data and accuracy decrease for older devices.