On Improving 5G Internet of Radio Light Security Based on LED Fingerprint Identification Method.
5G networks
LED fingerprint
security
visible light communication
Journal
Sensors (Basel, Switzerland)
ISSN: 1424-8220
Titre abrégé: Sensors (Basel)
Pays: Switzerland
ID NLM: 101204366
Informations de publication
Date de publication:
22 Feb 2021
22 Feb 2021
Historique:
received:
07
01
2021
revised:
14
02
2021
accepted:
16
02
2021
entrez:
6
3
2021
pubmed:
7
3
2021
medline:
7
3
2021
Statut:
epublish
Résumé
In this paper, a novel device identification method is proposed to improve the security of Visible Light Communication (VLC) in 5G networks. This method extracts the fingerprints of Light-Emitting Diodes (LEDs) to identify the devices accessing the 5G network. The extraction and identification mechanisms have been investigated from the theoretical perspective as well as verified experimentally. Moreover, a demonstration in a practical indoor VLC-based 5G network has been carried out to evaluate the feasibility and accuracy of this approach. The fingerprints of four identical white LEDs were extracted successfully from the received 5G NR (New Radio) signals. To perform identification, four types of machine-learning-based classifiers were employed and the resulting accuracy was up to 97.1%.
Identifiants
pubmed: 33671615
pii: s21041515
doi: 10.3390/s21041515
pmc: PMC7927084
pii:
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Subventions
Organisme : Horizon 2020 Framework Programme
ID : 761992
Références
Sensors (Basel). 2021 Feb 01;21(3):
pubmed: 33535421
Opt Express. 2015 Jan 26;23(2):1627-37
pubmed: 25835920
Sensors (Basel). 2019 Mar 07;19(5):
pubmed: 30866473
Sensors (Basel). 2021 Jan 24;21(3):
pubmed: 33498860
Sensors (Basel). 2020 May 24;20(10):
pubmed: 32456362
Sensors (Basel). 2020 Mar 03;20(5):
pubmed: 32138305
Sensors (Basel). 2021 Jan 28;21(3):
pubmed: 33525460