Finding a 'new'needle in the haystack: Unseen radio detection in large populations using deep learning
Radio frequency fingerprinting enhances security and privacy of wireless networks and
communications by learning and extracting unique characteristics embedded in transmitted …
communications by learning and extracting unique characteristics embedded in transmitted …
RadioNet: Robust deep-learning based radio fingerprinting
Radio fingerprinting identifies wireless devices by leveraging hardware imperfections
embedded in radio frequency (RF) signals. While neural networks have been applied to …
embedded in radio frequency (RF) signals. While neural networks have been applied to …
Attention is needed for RF fingerprinting
H Gu, L Su, W Zhang, C Ran - IEEE Access, 2023 - ieeexplore.ieee.org
Radio Frequency (RF) fingerprinting is a novel solution for identifying a unique radio from a
large pool of devices by analyzing the subtle characteristics that are inherent in the radio …
large pool of devices by analyzing the subtle characteristics that are inherent in the radio …
Dilated causal convolutional model for RF fingerprinting
J Robinson, S Kuzdeba, J Stankowicz… - 2020 10th Annual …, 2020 - ieeexplore.ieee.org
We design a network to classify individual wireless devices based on their radio frequency
(RF) fingerprints imparted on transmitted signals. The network combines a stack of dilated …
(RF) fingerprints imparted on transmitted signals. The network combines a stack of dilated …
Exposing the fingerprint: Dissecting the impact of the wireless channel on radio fingerprinting
Radio fingerprinting uniquely identifies wireless devices by leveraging tiny hardware-level
imperfections inevitably present in off-the-shelf radio circuitry. This way, devices can be …
imperfections inevitably present in off-the-shelf radio circuitry. This way, devices can be …
Deep complex networks for protocol-agnostic radio frequency device fingerprinting in the wild
Researchers have demonstrated various techniques for fingerprinting and identifying
devices. Previous approaches have identified devices from their network traffic or …
devices. Previous approaches have identified devices from their network traffic or …
Deep learning for RF fingerprinting: A massive experimental study
RF fingerprinting is a key security mechanism that allows device identification by learning
unchanging, hardware-based characteristics of the transmitter. In this article, we …
unchanging, hardware-based characteristics of the transmitter. In this article, we …
A comprehensive survey on radio frequency (RF) fingerprinting: Traditional approaches, deep learning, and open challenges
Fifth generation (5G) network and beyond envision massive Internet of Things (IoT) rollout to
support disruptive applications such as extended reality (XR), augmented/virtual reality …
support disruptive applications such as extended reality (XR), augmented/virtual reality …
Chameleons' oblivion: Complex-valued deep neural networks for protocol-agnostic RF device fingerprinting
Prior work has demonstrated techniques for fingerprinting devices based on their network
traffic or transmitted signals, which use software artifacts or characteristics of the underlying …
traffic or transmitted signals, which use software artifacts or characteristics of the underlying …
Riftnet: Radio frequency classification for large populations
J Robinson, S Kuzdeba - 2021 IEEE 18th Annual Consumer …, 2021 - ieeexplore.ieee.org
Radio transmitters can be identified by their unique radio frequency (RF) fingerprints.
Hardware differences and manufacturing variations between different RF devices impart the …
Hardware differences and manufacturing variations between different RF devices impart the …