A Novel Category Group Index Mechanism for Efficient Ranked Search of Encrypted Cloud Data

Nowadays, searchable encryption technology has become the focus of research. Owing to the enormous growth in data storage capacity arising from individual users, business organizations, enterprises and government agencies, it will take these data owners a great deal of time to construct and update indexes in the field of encrypted search in untrusted cloud environment. This has become an urgent problem to be solved. In this paper, based on multiple keywords ranked search, a novel category group index mechanism is proposed. By classifying documents, we create group vectors in each index which can not only transform a high-dimensional secret key into several low-dimensional keys to accelerate the process of encrypting indexes but also improve the flexibility of adding, modifying or deleting documents. When updating indexes, only the group vectors corresponding to the changed category keyword sets need to be updated. During the retrieval process of the proposed mechanism, a novel “targeted search” method is designed. With this method, instead of calculating the whole products, cloud server only needs to calculate some inner products of group vectors corresponding to query keywords in the trapdoor and each index to improve the search speed and efficiency. Extensive theoretical analysis and experiment results demonstrate that the method is more feasible and more effective than the compared schemes.