Computer Science

Computer Science ›› 2023, Vol. 50 ›› Issue (6A): 220200151-6.doi: 10.11896/jsjkx.220200151

• Network & Communication • Previous Articles     Next Articles

Tag Identification for UHF RFID Systems Based on Deep Learning

YU Jiabao1, YAO Junmei1, XIE Ruitao1, WU Kaishun1, MA Junchao2   

  1. 1 School of Computer and Software,Shenzhen University,Shenzhen,Guangdong 518000,China;
    2 School of Big Data and Internet,Shenzhen Technology University,Shenzhen,Guangdong 518000,China
  • Online:2023-06-10 Published:2023-06-12
  • About author:YU Jiabao,born in 1996,master.His main research interests include wireless device identification and deep learning. MA Junchao,born in 1983,associate professor,Ph.D,senior engineer.His main research interestsinclude big data,interest of things,and wireless ad hoc and sensor networks.
  • Supported by:
    National Natural Science Foundation of China(62072317,61802263),Guangdong Natural Science Foundation(2017A030312008),Faculty Research Fund of Shenzhen University(2019052,860/000002110322) and Natural Science Foundation of Top Talent of SZTU(20211061010016).

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Abstract: The most basic function of radio frequency identification(RFID) system is tag identification.However,the current authentication system cannot detect forged or cloned tags,which leads to potential security and privacy issues.At present,there are encryption based authentication protocols and feature extraction based solutions,among which encryption based authentication protocol is incompatible with existing protocols and feature extraction based authentication protocol has limitations such as difficulty in feature extraction or short recognition distance.This paper proposes a tag identification method for UHF RFID systems to overcome the two shortenings.The core idea is to first extract signals irrelevant to the logical information of tags from the backscattered RFID signals,and then send them to the convolutional neural network for similarity matching.According to the score of similarity matching and a given threshold,the authenticity of the tag is finally recognized.In this paper,we establish an experimental system which contains an USRP N210 used as the reader of the RFID system,and contains 150 UHF commercial tags to backscatter signals from the reader.We then collects the RFID signals based on this experiment.Experimental results show that the tag recognition accuracy based on deep learning can reach more than 94%,and its equal error ratio(EER) is 0.034 when the recognition distance is up to 2m.

Key words: Physical-layer identification, Radio frequency identification, Deep learning, Tag

CLC Number: 

  • TP391
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