Abstract
Specific emitter identification (SEI) designates the unique transmitter of a given signal, using only external feature measurements called the RF fingerprints of the signal. SEI is often used in military and civilian spectrum-management operations. The SEI technique has also been applied to enhance the security of wireless network, such as VHF radio networks, Wi-Fi networks, cognitive radios, and cellular networks and so on. According to the state of a given signal, SEI techniques can be split into two groups, namely transient signal techniques and steady state signal techniques. Owing to several challenges, transient signal techniques may be limited in practice. On the contrary, steady state signal techniques are more practical. In this paper, a SEI method belonging to steady state signal techniques is proposed. The method works based on the actual signal’s inherent nonlinear dynamical characteristics. Firstly, several measurements are acquired from the given signal. Secondly, permutation entropy is utilized to extract the nonlinear dynamical characteristics of these measurements as the signal’s RF fingerprint to identify the unique transmitter. DSSS-QPSK signals from WLAN cards, OFDM-BPSK, OFDM-16QAM, DSSS-CCK4b and DSSS-DQPSK signals from digital radios are used to evaluate the performance of the proposed method. Experimental results demonstrate that the proposed method is effective.
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Talbot, K., Duley, P., & Hyatt, M. (2003). Specific emitter identification and verification. Technology Review Journal, Spring/Summer, 113–133.
Ureten, O., & Serinken, N. (2007). Wireless security through RF fingerprinting. Canadian Journal of Electrical and Computer Engineering, 32(1), 27–33.
Brik, S. B. V., Gruteser, M., & Oh, S. (2008). Wireless device identification with radiometric signatures. In Proceedings of the 14th ACM international conference on mobile computing and networking (MobiCom08), (pp. 116–127). San Francisco, CA, USA.
Toonstra, J., & Kinsner, W. (1996). A radio transimitter fingerprinting system odo-1. In Proceedings of IEEE Canadian conference of electrical and computer engineering, (pp. 60–63), Calgary, Alta.
Shaw, D., & Kinsner, W. (1997). Multifractal modelling of radio transmitter transients for classification. In 1997 conference on communications, power and computing, (pp. 306–312), Winnipeg, MB.
Serinken, N., & Ureten, O. (2000). Generalised dimension characterisation of radio transmitter turn-on transients. Electronics Letters, 36(12), 1064–1066.
Ellis, K. J., & Serinken, N. (2001). Characteristics of radio transmitter fingerprints. Radio Science, 36, 585–597.
Hall, J., Barbeau, M., & Kranakis, E. (2004). Enhancing intrusion detection in wireless networks using radio frequency fingerprinting. In Proceedings of the 3rd IASTED international conference on communications, internet and information technology (CIIT), (pp. 201–206), St. Thomas, US Virgin Islands.
Hall, J., Barbeau, M., & Kranakis, E. (2006). Detecting rogue devices in bluetooth networks using radio frequency fingerprinting. In IASTED international conference on communications and computer networks, (pp. 1–6), Lima, Peru.
Richard, A. O., Kim, K., & Ahmad, A. (2009). On secure spectrum sensing in cognitive radio networks using emitters electromagnetic signature. In Proceedings of 18th international conference on computer communications and networks, (pp. 1–50), San Francisco, CA, USA.
Rehman, S. U., Sowerby, K., & Coghill, C. (2012). RF fingerprint extraction from the energy envelope of an instantaneous transient signal. In Australian communications theory workshop (pp. 90–95). New Zealand:Wellington.
Candore, A., Kocabas, O., & Koushanfar, F. (2009). Robust stable radiometric fingerprinting for wireless devices. In 2009 IEEE International workshop on hardware-oriented security and trust (HOST’09), (pp. 43–49), Francisco, CA.
Danev, B., Luecken, H., Capkun, S., & Defrawy, K. E. (2010). Attacks on physical-layer identification. In The third ACM conference on wireless network security (WiSec’10), (pp. 89–98), New York, USA.
Yuan, H. L., & Hu, A. Q. (2010). Preamble-based detection of wi-fi transmitter RF fingerprints. Electronics Letters, 46(16), 1165–1167.
Padilla, P., Padilla, J. L., & Valenzuela-Valdes, J. F. (2013). Radiofrequency identification of wireless devices based on RF fingerprinting. Electronics Letters, 49(22), 1409–1410.
Kennedy, I. O., Scanlon, P., Mullany, F. J., Buddhikot, M. M., Nolan, K. E., & Rondeau, T. W. (2008). Radio transmitter fingerprinting: a steady state frequency domain approach. In IEEE 68th vehicular technology conference (VTC 2008-Fall), (pp. 1–5), Calgary, AB, Canada.
Klein, R. W., Temple, M. A., & Mendenhalln, M. J. (2009). Application of wavelet-based RF fingerprinting to enhance wireless network security. Journal of Communications and Networks, 11(6), 544–555.
Yuan, Y., Huang, Z., Wu, H., & Wang, W. (2014). Specific emitter identification based on hilbert-huang transform-based time-frequency-energy distribution features. IET Communication, 8(13), 2404–2412.
Xu, S., Huang, B., Xu, L., & Xu, Z. (2007). Radio transmitter classification using a new method of stray features analysis combined with pca. In IEEE military communications conference (MILCOM2007) (pp. 1–5). Orlando, FL, USA.
Lu, X., Yang, J., & Zhou, Y. (2010). A new method based on local integral bispectra and svm for radio transmitter individual identification. In 2010 WASE international conference on information engineering, (pp. 65–68), Beidaihe, Hebei, China.
William, M. J. M., Suski, C, I. I., Temple, Michael A., & Mills, R. F. (2008). Radio frequency fingerprinting commercial communication devices to enhance electronic security. International Journal of Electronics Security and Digital Forensics, 1(3), 301–322.
Xu, S., Xu, Z., & Huang, B. (2008). Individual radio transmitter identification based on spurious modulation characteristic of signal envelop. In IEEE military communications conference (MILCOM2008) (pp. 1–5). San Diego, California.
Crystal, B. N., Bertoncini, Kevin Rudd, & Hinders, M. (2012). Wavelet fingerprinting of radio-frequency identification (RFID) tags. IEEE Transactions on Industrial Electronics, 59(12), 4843–4850.
Testing and troubleshooting digital RF communications transmitter designs, Agilent Technologies, 2002.
Carroll, T. L. (2007). A nonlinear dynamics method for signal identification. Chaos, 17(2), 1–7.
Bandt, C., & Pompe, B. (2002). Permutation entropy: A natural complexity measure for time series. Physical Review Letters, 88, 1–4.
Zunino, L., Perez, D. G., Martin, M. T., Garavaglia, M., Plastino, A., & Rosso, O. A. (2008). Permutation entropy of fractional brownian motion and fractional gaussian noise. Physics Letters A, 372(27), 4768–4774.
Cao, Y., Tung, W., Gao, J. B., Protopopescu, V. A., & Hively, L. M. (2004). Detecting dynamical changes in time series using the permutation entropy. Physical Review E, 70, 1–7.
Mcgill, R., Tukey, J. W., & Larsen, W. A. (1978). Variations of box plots. The American Statistician, 32(1), 12–16.
Williamson, D. F., Parker, R. A., & Kendrick, J. S. (1989). The boxplot: A simple visual method to interpret data. Annals of Internal Medicine, 110(11), 916–921.
Bishop, C. M. (2006). Pattern recognition and machine learning. New York, NY: Springer.
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Huang, G., Yuan, Y., Wang, X. et al. Specific Emitter Identification for Communications Transmitter Using Multi-measurements. Wireless Pers Commun 94, 1523–1542 (2017). https://doi.org/10.1007/s11277-016-3696-8
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DOI: https://doi.org/10.1007/s11277-016-3696-8