LoRa_RFFI_dataset

Citation Author(s):
Guanxiong
Shen
University of Liverpool
Junqing
Zhang
University of Liverpool
Alan
Marshall
University of Liverpool
Submitted by:
Guanxiong Shen
Last updated:
Tue, 05/17/2022 - 22:21
DOI:
10.21227/qqt4-kz19
Research Article Link:
Towards Scalable and Channel-Robust Radio Frequency Fingerprint Identification for LoRa
License:
Creative Commons Attribution
5897 Views
Categories:
Artificial Intelligence
IoT
Security
Keywords:
LoRa, Device Authentication, Radio Frequency Fingerprint Identification, Deep Learning
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Abstract 

This LoRa-RFFI project builds a LoRa radio frequency fingerprint identification (RFFI) system based on deep learning techniques. The RF signals are collected from 60 commercial-off-the-shelf LoRa devices. The packet preamble part and device labels are provided. The dataset consists of 19 sub-datasets and please refer to the README document for more detailed collection settings for all the sub-datasets.

More details are available at https://github.com/gxhen/LoRa_RFFI. Please cite the paper 'Towards Scalable and Channel-Robust Radio Frequency Fingerprint Identification for LoRa', IEEE Trans. Inf. Forensics Security (TIFS), 2022. 

Instructions: 

Please refer to the README documentation or https://github.com/gxhen/LoRa_RFFI.

Comments

for iiot datasets

Submitted by chander Nenavath on Mon, 02/14/2022 - 12:22

for lora datasets

Submitted by Amita Singh on Tue, 03/01/2022 - 06:13

for lora datasets

Submitted by orhan erdal on Wed, 03/09/2022 - 14:38

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Documentation

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File README_doc.pdf189.68 KB

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