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

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.