Privacy-preserving searchable encryption in the intelligent edge computing

Abstract

In intelligent edge computing, the private data of users are partly or entirely outsourced to the intelligent edge nodes for processing. To enforce security and privacy on edge network, data owners encrypt their private data and outsource it. It is particularly important to carry out efficient search and update on encrypted data. In this paper, we propose a searchable scheme to solve these problems on the intelligent edge network. Specially, we first propose S-HashMap index structure to make data update efficiently and safely while promising multi-keyword fuzzy ciphertext retrieval. Secondly, to measure the similarity between the query vector and the index nodes, we utilize the secure k-nearest neighbor to calculate the Euclidean distance. In addition to eliminating the necessity of pre-defined dictionaries, we achieve efficient multi-keyword fuzzy search and index updating without increasing search complexity. At the same time, this paper makes a thorough theoretical analysis and simulation of the proposed scheme. Compared with other schemes, we demonstrate that our scheme has better security and efficiency.