A Privacy Preserving Similarity Search Scheme over Encrypted High-Dimensional Data for Multiple Data Owners

Abstract

Cloud computing has become increasingly popular because of the benefits it provides. However, the security of the data stored in a remote cloud has become a major concern. For privacy concerns, searchable encryption (SE), which supports searching over encrypted data, has been proposed and developed rapidly in secure Boolean search and similarity search. However, most SE schemes can only support single data owner which is opposite to the condition in the cloud environment. In this paper, we employed locality-sensitive hashing (LSH) and bilinear map to deal with a privacy preserving similarity search for multiple data owners. In our scheme, data users can encrypt their data using their own secret keys. And the data users can perform the similarity search without knowing any information about the secret keys which belong to the data owners. We formally analyzed the security strength of our scheme. Extensive experiments on actual datasets showed that our scheme is extremely effective and efficient.