Radio Frequency Fingerprinting for Frequency Hopping Emitter Identification

In a frequency hopping spread spectrum (FHSS) network, the hopping pattern plays an important role in user authentication at the physical layer. However, recently, it has been possible to trace the hopping pattern through a blind estimation method for frequency hopping (FH) signals. If the hopping p...

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Autores principales:	Jusung Kang, Younghak Shin, Hyunku Lee, Jintae Park, Heungno Lee
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	frequency hopping signals radio frequency fingerprinting emitter identification outlier detection physical layer security inception block Technology T Engineering (General). Civil engineering (General) TA1-2040 Biology (General) QH301-705.5 Physics QC1-999 Chemistry QD1-999
Acceso en línea:	https://doaj.org/article/e353e3b285c04beeae016dad5d32e5e3
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spelling	oai:doaj.org-article:e353e3b285c04beeae016dad5d32e5e32021-11-25T16:38:38ZRadio Frequency Fingerprinting for Frequency Hopping Emitter Identification10.3390/app1122108122076-3417https://doaj.org/article/e353e3b285c04beeae016dad5d32e5e32021-11-01T00:00:00Zhttps://www.mdpi.com/2076-3417/11/22/10812https://doaj.org/toc/2076-3417In a frequency hopping spread spectrum (FHSS) network, the hopping pattern plays an important role in user authentication at the physical layer. However, recently, it has been possible to trace the hopping pattern through a blind estimation method for frequency hopping (FH) signals. If the hopping pattern can be reproduced, the attacker can imitate the FH signal and send the fake data to the FHSS system. To prevent this situation, a non-replicable authentication system that targets the physical layer of an FHSS network is required. In this study, a radio frequency fingerprinting-based emitter identification method targeting FH signals was proposed. A signal fingerprint (SF) was extracted and transformed into a spectrogram representing the time–frequency behavior of the SF. This spectrogram was trained on a deep inception network-based classifier, and an ensemble approach utilizing the multimodality of the SFs was applied. A detection algorithm was applied to the output vectors of the ensemble classifier for attacker detection. The results showed that the SF spectrogram can be effectively utilized to identify the emitter with 97% accuracy, and the output vectors of the classifier can be effectively utilized to detect the attacker with an area under the receiver operating characteristic curve of 0.99.Jusung KangYounghak ShinHyunku LeeJintae ParkHeungno LeeMDPI AGarticlefrequency hopping signalsradio frequency fingerprintingemitter identificationoutlier detectionphysical layer securityinception blockTechnologyTEngineering (General). Civil engineering (General)TA1-2040Biology (General)QH301-705.5PhysicsQC1-999ChemistryQD1-999ENApplied Sciences, Vol 11, Iss 10812, p 10812 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	frequency hopping signals radio frequency fingerprinting emitter identification outlier detection physical layer security inception block Technology T Engineering (General). Civil engineering (General) TA1-2040 Biology (General) QH301-705.5 Physics QC1-999 Chemistry QD1-999
spellingShingle	frequency hopping signals radio frequency fingerprinting emitter identification outlier detection physical layer security inception block Technology T Engineering (General). Civil engineering (General) TA1-2040 Biology (General) QH301-705.5 Physics QC1-999 Chemistry QD1-999 Jusung Kang Younghak Shin Hyunku Lee Jintae Park Heungno Lee Radio Frequency Fingerprinting for Frequency Hopping Emitter Identification
description	In a frequency hopping spread spectrum (FHSS) network, the hopping pattern plays an important role in user authentication at the physical layer. However, recently, it has been possible to trace the hopping pattern through a blind estimation method for frequency hopping (FH) signals. If the hopping pattern can be reproduced, the attacker can imitate the FH signal and send the fake data to the FHSS system. To prevent this situation, a non-replicable authentication system that targets the physical layer of an FHSS network is required. In this study, a radio frequency fingerprinting-based emitter identification method targeting FH signals was proposed. A signal fingerprint (SF) was extracted and transformed into a spectrogram representing the time–frequency behavior of the SF. This spectrogram was trained on a deep inception network-based classifier, and an ensemble approach utilizing the multimodality of the SFs was applied. A detection algorithm was applied to the output vectors of the ensemble classifier for attacker detection. The results showed that the SF spectrogram can be effectively utilized to identify the emitter with 97% accuracy, and the output vectors of the classifier can be effectively utilized to detect the attacker with an area under the receiver operating characteristic curve of 0.99.
format	article
author	Jusung Kang Younghak Shin Hyunku Lee Jintae Park Heungno Lee
author_facet	Jusung Kang Younghak Shin Hyunku Lee Jintae Park Heungno Lee
author_sort	Jusung Kang
title	Radio Frequency Fingerprinting for Frequency Hopping Emitter Identification
title_short	Radio Frequency Fingerprinting for Frequency Hopping Emitter Identification
title_full	Radio Frequency Fingerprinting for Frequency Hopping Emitter Identification
title_fullStr	Radio Frequency Fingerprinting for Frequency Hopping Emitter Identification
title_full_unstemmed	Radio Frequency Fingerprinting for Frequency Hopping Emitter Identification
title_sort	radio frequency fingerprinting for frequency hopping emitter identification
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/e353e3b285c04beeae016dad5d32e5e3
work_keys_str_mv	AT jusungkang radiofrequencyfingerprintingforfrequencyhoppingemitteridentification AT younghakshin radiofrequencyfingerprintingforfrequencyhoppingemitteridentification AT hyunkulee radiofrequencyfingerprintingforfrequencyhoppingemitteridentification AT jintaepark radiofrequencyfingerprintingforfrequencyhoppingemitteridentification AT heungnolee radiofrequencyfingerprintingforfrequencyhoppingemitteridentification
_version_	1718413109085863936

Radio Frequency Fingerprinting for Frequency Hopping Emitter Identification

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