Lightweight and Fine-Grained Privacy-Preserving Data Aggregation Scheme in Edge Computing

Abstract

Edge computing is a new computing paradigm, whichprovides computing resources at the edge of the network close to the data source and reduces the response delay and data transmission bandwidth. Data aggregation is a fundamental computing service in edge computing. However, existing data aggregation schemes do not consider the problem of fine-grained data aggregation. Besides, most schemes use a pair-based signature scheme, which cannot meet the actual situation of limited resources of terminal devices. In this article, we propose a lightweight, fine-grained privacy-preserving data aggregation scheme. The terminal devices add the user’s characteristic identifier bit in the generated message. Therefore, the edge servers can combine the characteristic identifiers in the messages to perform fine-grained data aggregation according to the aggregation rule list to obtain aggregated data of multiple target groups. We also use the unpaired signature scheme based on the elliptic curve, which has a faster signature and verification speed. Also, we use masks to avoid the privacy leakage of user’s characteristic identifiers. According to the experiments, the computation and communication overhead of our scheme is low. Simultaneously, the cloud center can dynamically update the aggregation rule list sent to the edge server according to the demands.