Fast and scalable counterfeits estimation for large-scale RFID systems

Gong, Wei, Stojmenovic, Ivan, Nayak, Amiya, Liu, Kebin and Liu, Haoxiang 2016, Fast and scalable counterfeits estimation for large-scale RFID systems, IEEE/ACM transactions on networking, vol. 24, no. 2, pp. 1052-1064, doi: 10.1109/TNET.2015.2406669.

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Title Fast and scalable counterfeits estimation for large-scale RFID systems
Author(s) Gong, Wei
Stojmenovic, Ivan
Nayak, Amiya
Liu, Kebin
Liu, Haoxiang
Journal name IEEE/ACM transactions on networking
Volume number 24
Issue number 2
Start page 1052
End page 1064
Total pages 13
Publisher IEEE
Place of publication Piscataway, N.J.
Publication date 2016-04
ISSN 1063-6692
Keyword(s) counterfeits estimation
informative counting
RFID tags
Summary Many algorithms have been introduced to deterministically authenticate Radio Frequency Identification (RFID) tags, while little work has been done to address scalability issue in batch authentications. Deterministic approaches verify tags one by one, and the communication overhead and time cost grow linearly with increasing size of tags. We design a fast and scalable counterfeits estimation scheme, INformative Counting (INC), which achieves sublinear authentication time and communication cost in batch verifications. The key novelty of INC builds on an FM-Sketch variant authentication synopsis that can capture key counting information using only sublinear space. With the help of this well-designed data structure, INC is able to provide authentication results with accurate estimates of the number of counterfeiting tags and genuine tags, while previous batch authentication methods merely provide 0/1 results indicating the existence of counterfeits. We conduct detailed theoretical analysis and extensive experiments to examine this design and the results show that INC significantly outperforms previous work in terms of effectiveness and efficiency.
Language eng
DOI 10.1109/TNET.2015.2406669
Field of Research 080501 Distributed and Grid Systems
Socio Economic Objective 970108 Expanding Knowledge in the Information and Computing Sciences
HERDC Research category C1.1 Refereed article in a scholarly journal
ERA Research output type C Journal article
Copyright notice ©2015, IEEE
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