Ncil (EPSRC). EPSRC-LWEC Challenge Fellowship EP/N02950X/1. Institutional Overview Board Statement: Not applicable. Informed Consent Statement:

Ncil (EPSRC). EPSRC-LWEC Challenge Fellowship EP/N02950X/1. Institutional Overview Board Statement: Not applicable. Informed Consent Statement: Not applicable. Data Availability Statement: Information happen to be published and access is available at https://doi.org/ 10.25919/131d-sj06. Acknowledgments: Tom Walsh, Suzanne Metcalfe, and Jason Wylie are thanked for their technical assistance. Conflicts of Interest: The authors declare no conflict of interest.
applied sciencesArticleRadio Frequency Fingerprinting for Frequency Hopping Emitter IdentificationJusung Kang 1 , Younghak Shin 2 , PK 11195 In stock Hyunku Lee three , Jintae Park four and Heungno Lee 1, 3School of Electrical Engineering and Laptop or computer Science, Gwangju Institute of Science and Technology, Gwangju 61005, Korea; [email protected] Department of Laptop Engineering, Mokpo National University, Muan-gun 58554, Korea; [email protected] LIG Nex1 Company Ltd., Yongin 16911, Korea; [email protected] Agency for Defense Improvement, Daejeon 34063, Korea; [email protected] Correspondence: [email protected]; Tel.: 82-62-715-Citation: Kang, J.; Shin, Y.; Lee, H.; Park, J.; Lee, H. Radio Frequency Fingerprinting for Frequency Hopping Emitter Identification. Appl. Sci. 2021, 11, 10812. https://doi.org/ 10.3390/app112210812 Academic Editor: Ernesto Limiti Received: eight October 2021 Accepted: 11 November 2021 Published: 16 NovemberAbstract: In a frequency hopping spread spectrum (FHSS) network, the hopping pattern plays an essential function in user authentication in the physical layer. Even so, recently, it has been possible to trace the hopping pattern through a blind estimation method for frequency hopping (FH) signals. If the hopping pattern is usually reproduced, the attacker can imitate the FH signal and send the fake information for the FHSS method. To stop this circumstance, a non-replicable authentication system that targets the physical layer of an FHSS network is required. In this study, a radio frequency fingerprintingbased emitter identification process targeting FH signals was proposed. A signal fingerprint (SF) was extracted and transformed into a spectrogram representing the time requency behavior in the SF. This spectrogram was trained on a deep inception network-based classifier, and an ensemble method utilizing the multimodality from the SFs was applied. A detection algorithm was applied to the output vectors in the ensemble classifier for attacker detection. The results showed that the SF spectrogram can be successfully utilized to determine the emitter with 97 accuracy, and the output vectors from the classifier is usually properly utilized to detect the attacker with an area below the receiver operating characteristic curve of 0.99. Keyword phrases: frequency hopping signals; radio frequency fingerprinting; emitter identification; outlier detection; physical layer security; inception block; deep Safranin Formula finding out classifier1. Introduction The most vital process in user authentication of a wireless communication method would be to identify the emitter information of RF signals. A frequent method to confirm the emitter facts, that’s, the emitter ID, is usually to decode the address field with the medium access handle (MAC) frame [1]. Having said that, beneath this digitized information-based authentication procedure on a MAC layer, an attacker can possess the address facts and imitate it as an authenticated user. To stop this weakness, a physical layer authentication course of action, namely radio frequency (RF) fingerprinting, has been studied in recent years.