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Efficient Detection of Cloned Attacks for Large-Scale RFID Systems

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Algorithms and Architectures for Parallel Processing (ICA3PP 2014)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 8630))

Abstract

This paper studies a practically important problem of cloned tag detection in large-scale RFID systems where an attacker compromises genuine tags and produces their replicas, namely cloned tags, to threaten RFID applications. Although many efforts have been made to address this problem, the existing work can hardly satisfy the stringent real-time requirement, and thus cannot catch cloning attacks in a time-efficient way. Moreover, the existing work does not consider energy-efficiency, which is very critical when battery-powered active tags are used. To fill these gaps, this paper proposes a Location Polling-based Cloned tag Detection (LP-CTD) protocol by taking both time-efficiency and energy-efficiency into consideration. LP-CTD reports the existence of cloned tags when the reader finds an expected singleton slot appearing as collision one. To improve the efficiency of detecting cloned tags, only sampled tags in LP-CTD participate in the detection process. Theoretical analysis on the proposed protocol is conducted to minimize their execution time and energy consumption. Extensive simulation experiments are conducted to evaluate the performance of the proposed protocols. The results demonstrate that the proposed LP-CTD protocol considerably outperforms the latest related protocols by reducing more than 80% of the execution time, and more than 90% of the energy consumption.

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Liu, X. et al. (2014). Efficient Detection of Cloned Attacks for Large-Scale RFID Systems. In: Sun, Xh., et al. Algorithms and Architectures for Parallel Processing. ICA3PP 2014. Lecture Notes in Computer Science, vol 8630. Springer, Cham. https://doi.org/10.1007/978-3-319-11197-1_7

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  • DOI: https://doi.org/10.1007/978-3-319-11197-1_7

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-11196-4

  • Online ISBN: 978-3-319-11197-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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