Browsing by Author "Uzundurukan, Emre"

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Citation Count: 1
Analysis of measurement instrumentation delay in modular experimental radar at C band
(Institute of Electrical and Electronics Engineers Inc., 2018) Abdulrazigh,M.Y.A.; Uzundurukan,E.; Kara,A.; Department of Electrical & Electronics Engineering; Airframe and Powerplant Maintenance
Unlike pulsed radars, Frequency-Modulated Continuous Wave (FMCW) radar emits continuously very low power levels with the same signal to noise ratio (SNR) of an equivalent pulsed radar. FMCW can measure range and speed of the target. In modular design of such radar, time delay is experienced due to modular components such as low-noise amplifiers (LNA), antennas and, especially, cables. This time delay causes frequency shifts in the measured beat frequency resulting a range measurement error. Therefore, this time delay has to be studied for accuracy of measurements. In this study, experimental results of range measurement errors of a FMCW radar operating at C band are presented. Considering time delay of modular components, a range error of approximately 0.1m was obtained within a range of 10m. © 2018 IEEE.
Citation Count: 1
Analysis of Measurement Instrumentation Delay in Modular Experimental Radar at C Band
(Ieee, 2018) Abdulrazigh, Mahfoud Y. A.; Uzundurukan, Emre; Kara, Ali; Department of Electrical & Electronics Engineering; Airframe and Powerplant Maintenance
Unlike pulsed radars, Frequency-Modulated Continuous Wave (FMCW) radar emits continuously very low power levels with the same signal to noise ratio (SNR) of an equivalent pulsed radar. FMCW can measure range and speed of the target. In modular design of such radar, time delay is experienced due to modular components such as low-noise amplifiers (LNA), antennas and, especially, cables. This time delay causes frequency shifts in the measured beat frequency resulting a range measurement error. Therefore, this time delay has to be studied for accuracy of measurements. In this study, experimental results of range measurement errors of a FMCW radar operating at C band are presented. Considering time delay of modular components, a range error of approximately 0.1m was obtained within a range of 10m.
Citation Count: 38
Assessment of Features and Classifiers for Bluetooth RF Fingerprinting
(Ieee-inst Electrical Electronics Engineers inc, 2019) Ali, Aysha M.; Uzundurukan, Emre; Kara, Ali; Department of Electrical & Electronics Engineering; Airframe and Powerplant Maintenance
Recently, network security has become a major challenge in communication networks. Most wireless networks are exposed to some penetrative attacks such as signal interception, spoofing, and stray. Radio frequency (RF) fingerprinting is considered to be a promising solution for network security problems and has been applied with various improvements. In this paper, extensive data from Bluetooth (BT) devices are utilized in RF fingerprinting implementation. Hilbert-Huang transform (HHT) has been used, for the first time, for RF fingerprinting of Bluetooth (BT) device identification. In this way, time-frequency-energy distributions (TFED) are utilized. By means of the signals' energy envelopes, the transient signals are detected with some improvements. Thirteen features are extracted from the signals' transients along with their TFEDs. The extracted features are pre-processed to evaluate their usability. The implementation of three different classifiers to the extracted features is provided for the first time in this paper. A comparative analysis based on the receiver operating characteristics (ROC) curves, the associated areas under curves (AUC), and confusion matrix are obtained to visualize the performance of the applied classifiers. In doing this, different levels of signal to noise ratio (SNR) levels are used to evaluate the robustness of the extracted features and the classifier performances. The classification performance demonstrates the feasibility of the method. The results of this paper may help readers assess the usability of RF fingerprinting for BT signals at the physical layer security of wireless networks.
Bluetooth sinyallerinin rf parmak izi için modüler ön uç tasarımı ve uygulaması
(2018) Uzundurukan, Emre; Kara, Ali; Department of Electrical & Electronics Engineering; Airframe and Powerplant Maintenance
Kablosuz ağlarda, üst düzey yazılım tabanlı güvenlik yöntemleri yetersiz kaldığında fiziksel katmanda alınan güvenlik önlemleri güvenliği tamamlayıcı olacaktır. Fiziksel katman yöntemlerinden biri Radyo Frekansı (RF) parmak izi yöntemidir. RF parmak izi yönteminde, parmak izi çıkarmak için yapılan veri toplama yöntemi kritik öneme sahiptir. Bu çalışmada, rafta hazır ticari ürün (RAHAT) ile tasarlanmış düşük maliyetli bir modüler RF ön ucu sunulmaktadır. Bu RF ön ucu tasarlamak için bilgisayar tabanlı tasarım aracı kullanılır. Önerilen RF ön uç kullanımı da dahil olmak üzere üç farklı veri toplama yöntemi de sunulmaktadır. Ayrıca, RF parmak izi performansı için RF ön ucunun üç farklı veri tabanına göre değerlendirilmesi sunulmaktadır. Bu veri tabanlarında geçici sinyal algılama, özellik çıkarma ve sınıflandırma algoritmaları uygulanmaktadır. Sınıflandırma, destekçi vektör makinesi ve yapay sinir ağları yöntemleri ile yapılmaktadır. Sonuçlar RF ön ucunun kullanılmasının doğru sınıflandırmaya ulaştığını göstermektedir.
Citation Count: 26
A Database for the Radio Frequency Fingerprinting of Bluetooth Devices
(Mdpi, 2020) Uzundurukan, Emre; Dalveren, Yaser; Kara, Ali; Department of Electrical & Electronics Engineering; Airframe and Powerplant Maintenance
Radio frequency fingerprinting (RFF) is a promising physical layer protection technique which can be used to defend wireless networks from malicious attacks. It is based on the use of the distinctive features of the physical waveforms (signals) transmitted from wireless devices in order to classify authorized users. The most important requirement to develop an RFF method is the existence of a precise, robust, and extensive database of the emitted signals. In this context, this paper introduces a database consisting of Bluetooth (BT) signals collected at different sampling rates from 27 different smartphones (six manufacturers with several models for each). Firstly, the data acquisition system to create the database is described in detail. Then, the two well-known methods based on transient BT signals are experimentally tested by using the provided data to check their solidity. The results show that the created database may be useful for many researchers working on the development of the RFF of BT devices.
Citation Count: 10
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.; Department of Electrical & Electronics Engineering; Airframe and Powerplant Maintenance
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.
Citation Count: 0
Design of Low-Cost Modular RF Front End for RF Fingerprinting of Bluetooth Signals
(Ieee, 2017) Uzundurukan, Emre; Ali, Aysha M.; Kara, Ali; Department of Electrical & Electronics Engineering; Airframe and Powerplant Maintenance
For RF fingerprinting of wireless devices, data acquisition has a critical role. Because of this, highly sophisticated devices arc 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.
Citation Count: 22
Improvements on transient signal detection for RF fingerprinting
(Institute of Electrical and Electronics Engineers Inc., 2017) Ali,A.M.; Uzundurukan,E.; Kara,A.; Department of Electrical & Electronics Engineering; Airframe and Powerplant Maintenance
The detection of the transient signal plays a significant role in RF fingerprinting for transmitter devices. This paper proposes modifications on two transient signal detection methods, namely, Bayesian change point detection and phase based detection. For initial tests, Bluetooth signals captured in the laboratory are used for performance analysis of the proposed methods. Preliminary results show that the proposed methods can be used in RF fingerprinting of wireless devices. © 2017 IEEE.
Citation Count: 0
Improvements on Transient Signal Detection for RF Fingerprinting
(Ieee, 2017) Ali, Aysha M.; Uzundurukan, Emre; Kara, Ali; Department of Electrical & Electronics Engineering; Airframe and Powerplant Maintenance
The detection of the transient signal plays a significant role in RF fingerprinting for transmitter devices. This paper proposes modifications on two transient signal detection methods, namely, Bayesian change point detection and phase based detection. For initial tests, Bluetooth signals captured in the laboratory are used for performance analysis of the proposed methods. Preliminary results show that the proposed methods can be used in RF fingerprinting of wireless devices.
Citation Count: 16
Performance Analysis of Modular RF Front End for RF Fingerprinting of Bluetooth Devices
(Springer, 2020) Uzundurukan, Emre; Ali, Aysha M.; Dalveren, Yaser; Kara, Ali; Department of Electrical & Electronics Engineering; Airframe and Powerplant Maintenance
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.