Title: VKSE-DO: verifiable keyword search over encrypted data for dynamic data-owner

Authors: Yinbin Miao; Jianfeng Ma; Fushan Wei; Kai Zhang; Zhiquan Liu

Addresses: State Key Laboratory of Integrated Services Networks, Xidian University, Shaanxi, Xi'an 710071, China ' State Key Laboratory of Integrated Services Networks, Xidian University, Shaanxi, Xi'an 710071, China ' State Key Laboratory of Integrated Services Networks, Xidian University, Shaanxi, Xi'an 710071, China ' State Key Laboratory of Integrated Services Networks, Xidian University, Shaanxi, Xi'an 710071, China ' State Key Laboratory of Integrated Services Networks, Xidian University, Shaanxi, Xi'an 710071, China

Abstract: With the popularity of cloud storage, search over encrypted data technique enables data-owner to securely store and efficiently retrieve ciphertext with a privacy-preserving way. However, in practice, the cloud service provider (CSP) is a semi-honest-but-curious entity which may honestly execute a fraction of search operations and return partial or incorrect search results to save its computation resources. Therefore, the searchable encryption (SE) scheme should provide the result verification mechanism to guarantee the correctness of search results. To the best of our knowledge, most of existing SE schemes rarely consider the dynamic data-owner scenario. Moreover, these schemes incur extra computational overhead when updating the whole ciphertext. To this end, we devise a secure and efficient cryptographic primitive called a verifiable keyword search over encrypted data for dynamic data-owner scheme. Formal security analysis proves that our scheme is secure against chosen keyword attack without random oracle. As a further contribution, experimental results over real-world dataset show its efficiency in practice.

Keywords: cloud storage; result verification; dynamic data-owner; chosen keyword attack.

DOI: 10.1504/IJHPCN.2018.093840

International Journal of High Performance Computing and Networking, 2018 Vol.12 No.1, pp.39 - 48

Available online: 27 Jul 2018 *

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