Analysis of receiver front end on the performance of RF fingerprinting

Radio Frequency (RF) fingerprinting is a technique, where a transmitter is identified from its electromagnetic emission. Most existing RF fingerprinting techniques have been evaluated with high-end receivers and promising classification results have been reported in the literature. However, the realization of RF fingerprinting in todays low-end (i.e. low cost) portable devices requires the validation of the existing RF fingerprinting techniques with low-end receivers. This contribution analyzes the performance of RF fingerprinting for low-end receivers. Experiments are performed for three transmitters and signals are captured with one high-end receiver and three low-end receivers using Universal Software Radio Peripheral (USRP). It is found that the classification accuracy of RF fingerprinting varies for different low-end receivers. Results show that low-end receivers provide good classification results at high receiver SNR but high receiver SNR is rare in a typical wireless communication environment. Whereas high-end receiver performs well even at low SNR.

[1]  Michael A. Temple,et al.  Improving Intra-Cellular Security Using Air Monitoring with RF Fingerprints , 2010, 2010 IEEE Wireless Communication and Networking Conference.

[2]  Robert F. Mills,et al.  Using Spectral Fingerprints to Improve Wireless Network Security , 2008, IEEE GLOBECOM 2008 - 2008 IEEE Global Telecommunications Conference.

[3]  Srdjan Capkun,et al.  Implications of radio fingerprinting on the security of sensor networks , 2007, 2007 Third International Conference on Security and Privacy in Communications Networks and the Workshops - SecureComm 2007.

[4]  Hsiao-Chun Wu,et al.  Physical layer security in wireless networks: a tutorial , 2011, IEEE Wireless Communications.

[5]  Witold Kinsner,et al.  A radio transmitter fingerprinting system ODO-1 , 1996, Proceedings of 1996 Canadian Conference on Electrical and Computer Engineering.

[6]  Irwin O. Kennedy,et al.  Feature extraction approaches to RF fingerprinting for device identification in femtocells , 2010, Bell Labs Technical Journal.

[7]  Oktay Ureten,et al.  Wireless security through RF fingerprinting , 2007, Canadian Journal of Electrical and Computer Engineering.

[8]  Robert F. Mills,et al.  Radio frequency fingerprinting commercial communication devices to enhance electronic security , 2008, Int. J. Electron. Secur. Digit. Forensics.

[9]  Kiseon Kim,et al.  On Secure Spectrum Sensing in Cognitive Radio Networks Using Emitters Electromagnetic Signature , 2009, 2009 Proceedings of 18th International Conference on Computer Communications and Networks.

[10]  Michael A. Jensen,et al.  Improved Radiometric Identification of Wireless Devices Using MIMO Transmission , 2011, IEEE Transactions on Information Forensics and Security.

[11]  Srdjan Capkun,et al.  Attacks on physical-layer identification , 2010, WiSec '10.

[12]  Srdjan Capkun,et al.  Physical-layer identification of UHF RFID tags , 2010, MobiCom.

[13]  Akbar Rahman,et al.  Exploiting the physical layer for enhanced security [Security and Privacy in Emerging Wireless Networks] , 2010, IEEE Wireless Communications.

[14]  Dennis Goeckel,et al.  Identifying Wireless Users via Transmitter Imperfections , 2011, IEEE Journal on Selected Areas in Communications.

[15]  Jeffrey H. Reed,et al.  Specific Emitter Identification for Cognitive Radio with Application to IEEE 802.11 , 2008, IEEE GLOBECOM 2008 - 2008 IEEE Global Telecommunications Conference.

[16]  Keith E. Nolan,et al.  Radio Transmitter Fingerprinting: A Steady State Frequency Domain Approach , 2008, 2008 IEEE 68th Vehicular Technology Conference.

[17]  Kevin W. Sowerby,et al.  RF fingerprint extraction from the energy envelope of an instantaneous transient signal , 2012, 2012 Australian Communications Theory Workshop (AusCTW).

[18]  R. Kędzierawski Universal software radio peripheral for ground penetrating radar prototyping , 2013 .