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Filters: Author is Jia, Xiaohua  [Clear All Filters]
2022-01-25
Wang, Mingyue, Miao, Yinbin, Guo, Yu, Wang, Cong, Huang, Hejiao, Jia, Xiaohua.  2021.  Attribute-based Encrypted Search for Multi-owner and Multi-user Model. ICC 2021 - IEEE International Conference on Communications. :1–7.
Nowadays, many data owners choose to outsource their data to public cloud servers while allowing authorized users to retrieve them. To protect data confidentiality from an untrusted cloud, many studies on searchable encryption (SE) are proposed for privacy-preserving search over encrypted data. However, most of the existing SE schemes only focus on the single-owner model. Users need to search one-by-one among data owners to retrieve relevant results even if data are from the same cloud server, which inevitably incurs unnecessary bandwidth and computation cost to users. Thus, how to enable efficient authorized search over multi-owner datasets remains to be fully explored. In this paper, we propose a new privacy-preserving search scheme for the multi-owner and multi-user model. Our proposed scheme has two main advantages: 1) We achieve an attribute-based keyword search for multi-owner model, where users can only search datasets from specific authorized owners. 2) Each data owner can enforce its own fine-grained access policy for users while an authorized user only needs to generate one trapdoor (i.e., encrypted search keyword) to search over multi-owner encrypted data. Through rigorous security analysis and performance evaluation, we demonstrate that our scheme is secure and feasible.