Searchable encryption (SE) techniques allow cloud clients to easily store data and search encrypted data in a privacy-preserving manner, where most of SE schemes treat the cloud server as honest-but-curious. However, in practice, the cloud server is a semi-honest-but-curious third-party, which only executes a fraction of search operations and returns a fraction of false search results to save its computational and bandwidth resources. Thus, it is important to provide a results verification method to guarantee the correctness of the search results. Existing SE schemes allow multiple data owners to upload different records to the cloud server, but these schemes have very high computational and storage overheads when applied in a different but more practical setting where each record is co-owned by multiple data owners. To address this problem, we develop a verifiable keyword search over encrypted data in multi-owner settings (VKSE-MO) scheme by exploiting the multisignatures technique. Thus, our scheme only requires a single index for each record and data users are assured of the correctness of the search results in challenging settings. Our formal security analysis proved that the VKSE-MO scheme is secure against a chosen-keyword attack under a random oracle model. In addition, our empirical study using a real-world dataset demonstrated the efficiency and feasibility of the proposed scheme in practice.
chosen-keyword attack, efficiency and feasibility, multi-owner settings, result verification, searchable encryption
Digital Communications and Networking | Information Security | Software Engineering
Science China Information Sciences
Springer Verlag (Germany)
MIAO, Yinbin; MA, Jianfeng; LIU, Ximeng; ZHANG, Junwei; and LIU, Zhiquan.
VKSE-MO: Verifiable keyword search over encrypted data in multi-owner settings. (2017). Science China Information Sciences. 60, (12), 1-15. Research Collection School Of Information Systems.
Available at: http://ink.library.smu.edu.sg/sis_research/3681
Creative Commons License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.