An Efficient Ranked Multi-Keyword Search for Multiple Data Owners Over Encrypted Cloud Data

Abstract

With the development of cloud storage, more data owners are inclined to outsource their data to cloud services. For privacy concerns, sensitive data should be encrypted before outsourcing. There are various searchable encryption schemes to ensure data availability. However, the existing search schemes pay little attention to the efficiency of data users' queries, especially for the multi-owner scenario. In this paper, we proposed a tree-based ranked multi-keyword search scheme for multiple data owners. Specifically, by considering a large amount of data in the cloud, we utilize the TF × IDF model to develop a multikeyword search and return the top-k ranked search results. To enable the cloud servers to perform a secure search without knowing any sensitive data (e.g., keywords and trapdoors), we construct a novel privacypreserving search protocol based on the bilinear mapping. To achieve an efficient search, for each data owner, a tree-based index encrypted with an additive order and privacy-preserving function family is constructed. The cloud server can then merge these indexes effectively, using the depth-first search algorithm to find the corresponding files. Finally, the rigorous security analysis proves that our scheme is secure, and the performance analysis demonstrates its efficacy and efficiency.