An Efficient Privacy-preserving Join-Aggregation Scheme in Smart Grids

Data aggregation is a common technique used in the Internet of Things (IoT) to combine fine-grained data from different sources. With increasing demands for data privacy, it has become a hot research topic. How to perform data aggregation without privacy leakage is a challenge. In smart grids, power data often has the characteristics of large volume and high sensitivity, while the limited computing resources of power bureaus can lead to corresponding delays and decreased service quality. This paper proposes an efficient and lightweight privacy-preserving scheme for data aggregation with the background of smart grid data aggregation. The proposed scheme ensures the privacy and security of sensitive data when processing join-aggregation task. The security of the scheme in the semi-honest model is proved using the Real-Ideal paradigm. Finally, the computational and communication costs of the proposed scheme are analyzed and compared, which shows that the total number of homomorphic operations is fewer than that of other related literature. The communication cost of the proposed scheme is four rounds, which is communication friendly.