Lightweight privacy-preserving data aggregation protocol against internal attacks in smart grid

Xiao Di Wang, Wei Zhi Meng, Yi Ning Liu*

*Corresponding author for this work

Research output: Contribution to journalJournal articleResearchpeer-review

Abstract

Privacy-preserving data aggregation has been studied extensively over the past decades, but there are still some concerns remained. For example, some schemes cannot resist against internal attacks, especially when the internal attack is launched by either the data centers that allocate the system security parameters or the attacker who shares the common information with the targeted user. In this paper, we propose a lightweight privacy-preserving data aggregation scheme, which is more efficient and suitable for the resource-constrained devices. Our scheme aggregates total electricity consumption data in the smart grid, with the capability of resisting against the collusion attacks with (n − 1) users. In the evaluation, we investigate the performances in the aspects of computation and communication costs as compared with the state-of-the-art, and the results show that our scheme is practical for the current smart grid environment.

Original languageEnglish
Article number102628
JournalJournal of Information Security and Applications
Volume55
Number of pages6
ISSN2214-2134
DOIs
Publication statusPublished - Dec 2020

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