Towards Length-Versatile and Noise-Robust Radio Frequency Fingerprint Identification

no code implementations • 6 Jul 2022 • Guanxiong Shen, Junqing Zhang, Alan Marshall, Mikko Valkama, Joseph Cavallaro

During the inference, a multi-packet inference approach is further leveraged to improve the classification accuracy in low SNR scenarios.

Data Augmentation

Towards Receiver-Agnostic and Collaborative Radio Frequency Fingerprint Identification

no code implementations • 6 Jul 2022 • Guanxiong Shen, Junqing Zhang, Alan Marshall, Roger Woods, Joseph Cavallaro, Liquan Chen

In this paper, we propose a receiver-agnostic RFFI system that is not sensitive to the changes in receiver characteristics; it is implemented by employing adversarial training to learn the receiver-independent features.

Collaborative Inference

Radio Frequency Fingerprint Identification for Security in Low-Cost IoT Devices

no code implementations • 28 Nov 2021 • Guanxiong Shen, Junqing Zhang, Alan Marshall, Mikko Valkama, Joseph Cavallaro

Data augmentation is adopted to improve low SNR RFFI performance.

Data Augmentation

Towards Scalable and Channel-Robust Radio Frequency Fingerprint Identification for LoRa

no code implementations • 6 Jul 2021 • Guanxiong Shen, Junqing Zhang, Alan Marshall, Joseph Cavallaro

Radio frequency fingerprint identification (RFFI) is a promising device authentication technique based on the transmitter hardware impairments.

Data Augmentation Metric Learning

Radio Frequency Fingerprint Identification for LoRa Using Spectrogram and CNN

no code implementations • 30 Dec 2020 • Guanxiong Shen, Junqing Zhang, Alan Marshall, Linning Peng, Xianbin Wang

Radio frequency fingerprint identification (RFFI) is an emerging device authentication technique that relies on intrinsic hardware characteristics of wireless devices.