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COAR Access Rights: metadata only accessSubject: RF fingerprinting

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    Conference Object
    Citation - Scopus: 11
    Design of Low-Cost Modular Rf Front End for Rf Fingerprinting of Bluetooth Signals
    (Institute of Electrical and Electronics Engineers Inc., 2017) Uzundurukan,E.; Ali,A.M.; Kara,A.
    For RF fingerprinting of wireless devices, data acquisition has a critical role. Because of this, highly sophisticated devices are used for data capturing or acquisition. In this paper, design of a RF receiver front end with modular components is presented. This design contains filtering and down conversion processing of Bluetooth signals for cellular phones. Moreover, AWR VSS and MATLAB have been used for simulating the down converter circuit. With this simulation, effects of components that used in the design on recorded signal have been observed. In this work in progress paper, only high SNR conditions are considered. © 2017 IEEE.
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    Conference Object
    Citation - Scopus: 6
    A Mini-Review on Radio Frequency Fingerprinting Localization in Outdoor Environments: Recent Advances and Challenges
    (Institute of Electrical and Electronics Engineers Inc., 2022) Dogan,D.; Dalveren,Y.; Kara,A.
    A considerable growth in demand for locating the source of emissions in outdoor environments has led to the rapid development of various localization methods. Among these, RF fingerprinting (RFF) localization has become one of the most promising method due to its unique advantages resulted from the recent developments in machine learning techniques. In this short review, it is aimed to assess the existing RFF methods in the literature for outdoor localization. For this purpose, firstly, the current state of RFF localization methods in outdoor environments are overviewed. Then, the main research challenges in the development of RFF localization are highlighted. This is followed by a brief discussion on the open issues in order to give future research directions. Furthermore, the research efforts currently undertaken by the authors are briefly addressed. © 2022 IEEE.
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    Article
    Citation - WoS: 11
    Citation - Scopus: 15
    A Study on the Performance Evaluation of Wavelet Decomposition in Transient-Based Radio Frequency Fingerprinting of Bluetooth Devices
    (Wiley, 2022) Almashaqbeh, Hemam; Dalveren, Yaser; Kara, Ali
    Radio frequency fingerprinting (RFF) is used as a physical-layer security method to provide security in wireless networks. Basically, it exploits the distinctive features (fingerprints) extracted from the physical waveforms emitted from radio devices in the network. One of the major challenges in RFF is to create robust features forming the fingerprints of radio devices. Here, dual-tree complex wavelet transform (DT-CWT) provides an accurate way of extracting those robust features. However, its performance on the RFF of Bluetooth transients which fall into narrowband signaling has not been reported yet. Therefore, this study examines the performance of DT-CWT features on the use of transient-based RFF of Bluetooth devices. Initially, experimentally collected Bluetooth transients from different smartphones are decomposed by DT-CWT. Then, the characteristics and statistics of the wavelet domain signal are exploited to create robust features. Next, the support vector machine (SVM) is used to classify the smartphones. The classification accuracy is demonstrated by varying channel signal-to-noise ratio (SNR) and the size of transient duration. Results show that reasonable accuracy can be achieved (lower bound of 88%) even with short transient duration (1024 samples) at low SNRs (0-5 dB).