Design of a Channel Robust Radio Frequency Fingerprint Identification Scheme

被引:11
|
作者
Xing, Yuexiu [1 ]
Hu, Aiqun [2 ,3 ]
Zhang, Junqing [4 ]
Peng, Linning [5 ,6 ]
Wang, Xianbin [7 ]
机构
[1] Nanjing Univ Posts & Telecommun, Sch Internet Things, Nanjing 210003, Peoples R China
[2] Southeast Univ, Sch Informat Sci & Engn, Nanjing 210096, Peoples R China
[3] Frontier Crossing Sci Res Ctr, Purple Mt Labs Network & Commun Secur, Nanjing 210096, Peoples R China
[4] Univ Liverpool, Dept Elect Engn & Elect, Liverpool L69 3GJ, England
[5] Southeast Univ, Sch Cyber Sci & Engn, Nanjing 210096, Peoples R China
[6] Purple Mt Labs Network & Commun Secur, Nanjing 210096, Peoples R China
[7] Western Univ, Dept Elect & Comp Engn, London, ON N6A 5B9, Canada
来源
IEEE INTERNET OF THINGS JOURNAL | 2023年 / 10卷 / 08期
关键词
Symbols; Feature extraction; Wireless fidelity; Wireless communication; OFDM; Internet of Things; Authentication; 802.11; device authentication; orthogonal frequency division multiplexing (OFDM); radio frequency fingerprint (RFF); wireless channel; INTERNET; SYSTEMS;
D O I
10.1109/JIOT.2022.3228280
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Radio frequency fingerprint (RFF) identification is an emerging device authentication technique that exploits the hardware imperfections resulting from the manufacturing process. Due to the varying impact of the wireless channel during RFF training and test stages, it is challenging to design channel-independent RFF techniques. This article designs a channel robust RFF identification scheme by leveraging the different spectrum of adjacent signal symbols, named the Difference of the Logarithm of the Spectrum (DoLoS), which does not rely on a single RFF feature or requires additional manipulation of the devices under test. Specifically, DoLoS exploits the fact that two different symbols in a packet exhibit different RFF features but have a similar channel response during the channel coherence time. We implemented the DoLoS with the IEEE 802.11 orthogonal frequency division multiplexing (OFDM) system as a case study. We carried out extensive experiments using seven Wi-Fi devices of the same model in different wireless channel environments, including 12 data collection positions in two completely different environments. Compared with conventional RFF identification schemes that do not eliminate channel effects, our scheme is robust to channel variations and the highest identification accuracy is 99.02% in the single-environment evaluation and 97.05% in the cross-environment evaluation.
引用
收藏
页码:6946 / 6959
页数:14
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