An efficient and secure aggregation encryption scheme in edge computing

Abstract

Edge computing is a highly virtualized paradigm that can services the Internet of Things(IoT) devices more efficiently. It is a non-trivial extension of cloud computing, which can not only meet the big data processing requirements of cloud computing, but also collect and analyze distributed data. However, it inherits many security and privacy challenges of cloud computing, such as: authentication and access control. To address these problem, we proposed a new efficient privacy-preserving aggregation scheme for edge computing. Our scheme consists of two steps. First, we divided the data of the end users with the Simulated Annealing Module Partition (SAMP) algorithm. And then, the end sensors and edge nodes performed respectively differential aggregation mechanism with the Differential Aggregation Encryption (DAE) algorithm which can make noise interference and encryption algorithm with trusted authority (TA). Experiment results show that the DAE can preserve user privacy, and has significantly less computation and communication overhead than existing approaches.