Wireless Personal Communications

, Volume 103, Issue 1, pp 133–143 | Cite as

A New Scalable Lightweight Grouping Proof Protocol for RFID systems

  • Wei Zhang
  • Shiming Qin
  • Shengming Wang
  • Longkai Wu
  • Baolin Yi


Radio-frequency Identification (RFID) grouping proof protocol is widely used in medical healthcare industry, transportation industry, crime forensics and so on,it is a research focus in the field of information security. The RFID grouping proof protocol is to prove that some tags belong to the same group and exist simultaneously. To improve the applicability of the RFID grouping proof protocol in low cost tag applications, this paper proposes a new scalable lightweight RFID grouping proof protocol. Tags in the proposed protocol only generate pseudorandom numbers and execute exclusive-or(XOR) operations. An anti-collision algorithm based on adaptive 4-ary pruning query tree (A4PQT) is used to identify the response message of tags. Updates to secret information in tags are kept synchronized with the verifier during the entire grouping proof process. Based on these innovations, the proposed protocol resolves the scalability issue for low-cost tag systems and improves the efficiency and security of the authentication that is generated by the grouping proof. Compared with other state-of-the art protocols, it is shows that the proposed protocol requires lower tag-side computational complexity, thereby achieving an effective balance between protocol security and efficiency.


RFID Grouping proof Security Computational cost Authentication 



We would like to thank the editor and anonymous reviewers for their valuable suggestions. This research was funded by visualization technology research and demonstration platform of Local Chronicles (2015BAK07B03), National Key R&D Plan (2017YFB1401300).


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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  • Wei Zhang
    • 1
  • Shiming Qin
    • 1
  • Shengming Wang
    • 1
  • Longkai Wu
    • 2
  • Baolin Yi
    • 1
  1. 1.National Engineering Research Center for E-LearningCentral China Normal UniversityWuhanChina
  2. 2.National Institute of EducationNanyang Technological UniversitySingaporeSingapore

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