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An Enhanced Anonymous Identification Scheme for Smart Grids

  • Shanshan Ge
  • Peng ZengEmail author
  • Kim-Kwang Raymond Choo
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 580)

Abstract

In smart grid communications, preserving the privacy of consumers’ electricity usage data is a topic of interest for power providers and consumers, as well as regulators. Sui (IEEE Trans. Smart Grid, 2016) proposed a new threshold-based anonymous identification (TAI) scheme for smart grid communications and claimed that TAI scheme achieves unlinkability, strong anonymity, non-frameability, identification, and integrity. In this paper, however, we demonstrate that due to a flawed Decisional Diffie–Hellman assumption in a bilinear group, TAI scheme is unlikely to achieve unlinkability, in violation of their security claims. Specifically, an adversary \( {\mathcal{A}} \) can easily link different consumption reports from the same consumer during the anonymous consumption reporting part and link a disavowal proof of a compliant smart meter to its previous signature. We then propose an enhanced anonymous identification scheme to eliminate the security vulnerability in the scheme, in the sense that no one can determine whether two different consumption reports are from the same consumer.

Keywords

Smart grid Privacy-preserving Unlinkability Demand-response Identification 

Notes

Acknowledgment

P. Zeng is the corresponding author. The work is supported in part by the NSFC-Zhejiang Joint Fund for the Integration of Industrialization and Informatization under Grant No. U1509219, the Shanghai Natural Science Foundation under Grant No. 17ZR1408400, the National Natural Science Foundation of China under Grant No. 61632012, and the Shanghai Sailing Program under Grant No. 17YF1404300.

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Copyright information

© Springer International Publishing AG 2018

Authors and Affiliations

  • Shanshan Ge
    • 1
  • Peng Zeng
    • 1
    Email author
  • Kim-Kwang Raymond Choo
    • 2
  1. 1.The Shanghai Key Laboratory of Trustworthy ComputingEast China Normal UniversityShanghaiChina
  2. 2.The Department of Information Systems and Cyber SecurityUniversity of Texas at San AntonioSan AntonioUSA

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