A new differentially private data aggregation with fault tolerance for smart grid communications

Haiyong Bao, Rongxing Lu

Research output: Contribution to journalArticlepeer-review

133 Scopus citations

Abstract

Privacy-preserving data aggregation has been widely studied to meet the requirement of timely monitoring measurements of users while protecting individual's privacy in smart grid communications. In this paper, a new secure data aggregation scheme, named differentially private data aggregation with fault tolerance (DPAFT), is proposed, which can achieve differential privacy and fault tolerance simultaneously. Specifically, inspired by the idea of Diffie-Hellman key exchange protocol, an artful constraint relation is constructed for data aggregation. With this novel constraint, DPAFT can support fault tolerance of malfunctioning smart meters efficiently and flexibly. In addition, DPAFT is also enhanced to resist against differential attacks, which are suffered in most of the existing data aggregation schemes. By improving the basic Boneh-Goh-Nissim cryptosystem to be more applicable to the practical scenarios, DPAFT can resist much stronger adversaries, i.e., user's privacy can be protected in the honest-but-curious model. Extensive performance evaluations are further conducted to illustrate that DPAFT outperforms the state-of-the-art data aggregation schemes in terms of storage cost, computation complexity, utility of differential privacy, robustness of fault tolerance, and the efficiency of user addition and removal.

Original languageEnglish
Article number07060705
Pages (from-to)248-258
Number of pages11
JournalIEEE Internet of Things Journal
Volume2
Issue number3
DOIs
StatePublished - 1 Jun 2015
Externally publishedYes

Keywords

  • Smart grid
  • differential privacy
  • fault tolerance
  • privacy-preserving

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