Practical Attribute-Based Multi-Keyword Ranked Search Scheme in Cloud Computing

Attribute-based keyword search (ABKS) has a broad developing prospect in providing search service for users and realizing fine-grained access control over ciphertext in the background of cloud computing. However, two open problems prevent further development and application of ABKS. First, most of ABKS schemes suffer from inside keyword guessing attack (KGA) inherently, which is a great threat to the security of the scheme. Second, the existing ABKS schemes focus on single or conjunctive keyword search, these inflexible retrieval modes may lead to efficiency loss caused by inaccurate positioning of user's interest and greatly reduce user search experience. In this article, we introduce a semi-trusted server and build a dual server model. Based on the dual server model and our proposed techniques, we are the first to put forward an attribute-based multi-keyword ranked search scheme against inside keyword guessing attack (ABKRS-KGA) to solve the mentioned two problems simultaneously. In our scheme, the queries of users contain weighted keywords and the returned files can be ranked according to user's query interest. We provide strict security definitions for two types of adversaries and we are the first to prove that the construction is adaptively secure against both chosen-keyword attack (CKA) and KGA. Finally, all-side simulation with real-world data set is implemented for the proposed scheme, and the simulation results show that the efficiency of the proposed scheme is acceptable.