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Entropy 2017, 19(3), 117; doi:10.3390/e19030117

Specific Emitter Identification Based on the Natural Measure

1
Center for Cyber Security, School of Electronic Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China
2
Southwest Electronics and Telecommunication Technology Research Institute, Chengdu 611731, China
*
Author to whom correspondence should be addressed.
Academic Editors: Raúl Alcaraz Martínez and Kevin H. Knuth
Received: 15 December 2016 / Revised: 5 March 2017 / Accepted: 9 March 2017 / Published: 15 March 2017
(This article belongs to the Section Information Theory)
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Abstract

Specific emitter identification (SEI) techniques are often used in civilian and military spectrum-management operations, and they are also applied to support the security and authentication of wireless communication. In this letter, a new SEI method based on the natural measure of the one-dimensional component of the chaotic system is proposed. We find that the natural measures of the one-dimensional components of higher dimensional systems exist and that they are quite diverse for different systems. Based on this principle, the natural measure is used as an RF fingerprint in this letter. The natural measure can solve the problems caused by a small amount of data and a low sample rate. The Kullback–Leibler divergence is used to quantify the difference between the natural measures obtained from diverse emitters and classify them. The data obtained from real application are exploited to test the validity of the proposed method. Experimental results show that the proposed method is not only easy to operate, but also quite effective, even though the amount of data is small and the sample rate is low. View Full-Text
Keywords: specific emitter identification; radio frequency fingerprint; Kullback–Leibler divergence; natural measure specific emitter identification; radio frequency fingerprint; Kullback–Leibler divergence; natural measure
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Jia, Y.; Zhu, S.; Gan, L. Specific Emitter Identification Based on the Natural Measure. Entropy 2017, 19, 117.

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