Performance Analysis of Modular Rf Front End for Rf Fingerprinting of Bluetooth Devices

dc.authorid Kara, Ali/0000-0002-9739-7619
dc.authorid Dalveren, Yaser/0000-0002-9459-0042
dc.authorid UZUNDURUKAN, Emre/0000-0003-4868-9639
dc.authorscopusid 57195223293
dc.authorscopusid 57195218811
dc.authorscopusid 51763497600
dc.authorscopusid 7102824862
dc.authorwosid Kara, Ali/R-8038-2019
dc.contributor.author Uzundurukan, Emre
dc.contributor.author Ali, Aysha M.
dc.contributor.author Dalveren, Yaser
dc.contributor.author Kara, Ali
dc.contributor.other Department of Electrical & Electronics Engineering
dc.contributor.other Airframe and Powerplant Maintenance
dc.date.accessioned 2024-07-05T15:38:09Z
dc.date.available 2024-07-05T15:38:09Z
dc.date.issued 2020
dc.department Atılım University en_US
dc.department-temp [Uzundurukan, Emre; Dalveren, Yaser] Atilim Univ, Dept Avion, TR-06830 Ankara, Turkey; [Ali, Aysha M.] Omer Al Mukhtar Univ, Dept Elect & Elect Engn, Al Bayda, Libya; [Dalveren, Yaser] Norwegian Univ Sci & Technol, Fac Informat Technol & Elect Engn, Dept Elect Syst, Gjovik, Norway; [Kara, Ali] Atilim Univ, Elect & Elect Engn Dept, TR-06830 Ankara, Turkey en_US
dc.description Kara, Ali/0000-0002-9739-7619; Dalveren, Yaser/0000-0002-9459-0042; UZUNDURUKAN, Emre/0000-0003-4868-9639 en_US
dc.description.abstract Radio frequency fingerprinting (RFF) could provide an efficient solution to address the security issues in wireless networks. The data acquisition system constitutes an important part of RFF. In this context, this paper presents an implementation of a modular RF front end system to be used in data acquisition for RFF. Modularity of the system provides flexible implementation options to suit diverse frequency bands with different applications. Moreover, the system is able to collect data by means of any digitizer, and enable to record the data at lower frequencies. Therefore, proposed RF front end system becomes a low-cost alternative to existing devices used in data acquisition. In its implementation, Bluetooth (BT) signals were used. Initially, transients of BT signals were detected by utilizing a large number of BT devices (smartphones). From the detected transients, distinctive signal features were extracted. Then, support vector machine (SVM) and neural networks (NN) classifiers were implemented to the extracted features for evaluating the feasibility of proposed system in RFF. As a result, 96.9% and 96.5% classification accuracies on BT devices have been demonstrated for SVM and NN classifiers respectively. en_US
dc.identifier.citationcount 16
dc.identifier.doi 10.1007/s11277-020-07162-z
dc.identifier.endpage 2531 en_US
dc.identifier.issn 0929-6212
dc.identifier.issn 1572-834X
dc.identifier.issue 4 en_US
dc.identifier.scopus 2-s2.0-85078210176
dc.identifier.startpage 2519 en_US
dc.identifier.uri https://doi.org/10.1007/s11277-020-07162-z
dc.identifier.uri https://hdl.handle.net/20.500.14411/3052
dc.identifier.volume 112 en_US
dc.identifier.wos WOS:000540219800023
dc.identifier.wosquality Q3
dc.institutionauthor Uzundurukan, Emre
dc.institutionauthor Dalveren, Yaser
dc.institutionauthor Kara, Ali
dc.language.iso en en_US
dc.publisher Springer en_US
dc.relation.publicationcategory Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı en_US
dc.rights info:eu-repo/semantics/closedAccess en_US
dc.scopus.citedbyCount 15
dc.subject Radio frequency fingerprinting en_US
dc.subject Bluetooth en_US
dc.subject Data acquisition en_US
dc.subject RF front end en_US
dc.subject Support vector machine en_US
dc.subject Neural networks en_US
dc.title Performance Analysis of Modular Rf Front End for Rf Fingerprinting of Bluetooth Devices en_US
dc.type Article en_US
dc.wos.citedbyCount 15
dspace.entity.type Publication
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