Academy & Industry Research Collaboration Center (AIRCC)

Volume 10, Number 10, July 2020

Using SDR Platform to Extract the RF Fingerprint of the Wireless Devices for Device Identification


Ting-Yu Lin, Chia-Min Lai and Chi-Wei Chen, Institute for Information Industry, Taiwan


Due to the advent of the Internet of Things era, the number of related wireless devices is increasing, making the abundant and complex information networks formed by communication between devices. Therefore, security and trust between devices a huge challenge. In the traditional identification method, there are identifiers such as hash-based message authentication code, key, and so on, often used to mark a message that the receiving end can verify it. However, this kind of identifiers is easy to tamper. Therefore, recently researchers address the idea that using RF fingerprint, also called radio frequency fingerprint, for identification. Our paper demonstrates a method that extracts properties and identifies each device. We achieved a high identification rate, 99.9% accuracy in our experiments where the devices communicate with Wi-Fi protocol. The proposed method can be used as a stand-alone identification feature, or for two-factor authentication.


Internet-of-Things (IoT), Authentication, RF fingerprint, Machine Learning (ML), Device Identification.