Decentralized attribute-based conjunctive keyword search scheme with online/offline encryption and outsource decryption for cloud computing

Abstract

In recent years, the increasing popularity of cloud computing has led to a trend that data owners prefer to outsource their data to the clouds for the enjoyment of the on-demand storage and computing services. For security and privacy concerns, fine-grained access control and secure data retrieval for the outsourced data is of critical importance. Attribute-based keyword search (ABKS) scheme, as a cryptographic primitive which explores the notion of public key encryption with keyword search (PEKS) into the context of attribute-based encryption (ABE), can enable the data owner to flexibly share his data to a specified group of users satisfying the access policy and meanwhile, maintain the confidentiality and searchable properties of the sensitive data. However, in most of the previous ABKS schemes, the decryption service is not provided, and a fully trusted central authority is required, which is not practical in the scenario that the access policy is written over attributes or credentials issued across different trust domains and organizations. Moreover, the efficiency of storage and computation is also the bottleneck of implementation of ABKS scheme. In this paper, for the first time, we propose a decentralized ABKS scheme with conjunctive keyword search for the cloud storage system. Besides the multi-keyword search in the decentralized setting, our scheme outsources the undesirable costly operations of decryption to the cloud without degrading the user’s privacy. Furthermore, the encryption phase is also divided into two phases, an offline pre-computation phase which is independent with the plaintext message, access policy, and keyword set, and can be performed at any time when the data owner’s device is otherwise not in use, and an online encryption phase which only incurs very little computation costs. Security analysis indicates that our scheme is provably secure in the random oracle model. The asymptotic complexity comparison and simulation results also show that our scheme achieves high computation efficiency.