Machine learning for the detection and identification of Internet of Things devices: A survey

Y Liu, J Wang, J Li, S Niu… - IEEE Internet of Things …, 2021 - ieeexplore.ieee.org
The Internet of Things (IoT) is becoming an indispensable part of everyday life, enabling a
variety of emerging services and applications. However, the presence of rogue IoT devices …

Radio frequency fingerprint identification for narrowband systems, modelling and classification

J Zhang, R Woods, M Sandell… - IEEE Transactions …, 2021 - ieeexplore.ieee.org
Device authentication is essential for securing Internet of things. Radio frequency fingerprint
identification (RFFI) is an emerging technique that exploits intrinsic and unique hardware …

Specific emitter identification with limited samples: A model-agnostic meta-learning approach

N Yang, B Zhang, G Ding, Y Wei, G Wei… - IEEE …, 2021 - ieeexplore.ieee.org
It is necessary but difficult to obtain a large number of labeled samples to train the
classification model in many real scenes. This letter proposes an approach for specific …

Radio frequency fingerprint identification based on denoising autoencoders

J Yu, A Hu, F Zhou, Y Xing, Y Yu, G Li… - … on Wireless and …, 2019 - ieeexplore.ieee.org
Radio Frequency Fingerprinting (RFF) is one of the promising passive authentication
approaches for improving the security of the Internet of Things (IoT). However, with the …

Open set wireless transmitter authorization: Deep learning approaches and dataset considerations

S Hanna, S Karunaratne… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
Due to imperfections in transmitters' hardware, wireless signals can be used to verify their
identity in an authorization system. While deep learning was proposed for transmitter …

Radio frequency fingerprinting exploiting non-linear memory effect

Y Li, Y Ding, J Zhang, G Goussetis… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Radio frequency fingerprint (RFF) identification distinguishes wireless transmitters by
exploiting their hardware imperfection that is inherent in typical radio frequency (RF) front …

Radio-frequency fingerprint extraction based on feature inhomogeneity

L Sun, X Wang, Z Huang, B Li - IEEE Internet of Things Journal, 2022 - ieeexplore.ieee.org
With the popularization of the Internet of Things (IoT), its security has become increasingly
prominent. Radio-frequency fingerprinting (RFF) is a promising approach to identify a …

Deep learning based RF fingerprint identification with channel effects mitigation

H Fu, L Peng, M Liu, A Hu - IEEE Open Journal of the …, 2023 - ieeexplore.ieee.org
The radio frequency fingerprint (RFF)-based device identification is a promising physical
layer authentication technique. However, the wireless channel significantly affects the RFF …

Penetrating RF fingerprinting-based authentication with a generative adversarial attack

S Karunaratne, E Krijestorac… - ICC 2021-IEEE …, 2021 - ieeexplore.ieee.org
Physical layer authentication relies on detecting unique imperfections in signals transmitted
by radio devices to isolate their fingerprint. Recently, deep learning-based authenticators …

Wireless fingerprinting via deep learning: The impact of confounding factors

M Cekic, S Gopalakrishnan… - 2021 55th Asilomar …, 2021 - ieeexplore.ieee.org
Can we distinguish between two wireless transmitters sending exactly the same message,
using the same protocol? The opportunity for doing so arises due to subtle nonlinear …