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Privacy-Preserving Search Over Encrypted Personal Health Record In Multi-Source Cloud

Xin Yao, Yaping Lin, Qin Liu and 1 more

IEEE Access · 2018

doi:10.1109/access.2018.2793304 (opens in a new tab)

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Abstract

Cloud-based Personal Health Record systems (CB-PHR) have great potential in facilitating the management of individual health records. Security and privacy concerns are among the main obstacles for the wide adoption of CB-PHR systems. In this paper, we consider a multi-source CB-PHR system in which multiple data providers, such as hospitals and physicians are authorized by individual data owners to upload their personal health data to an untrusted public cloud. The health data are submitted in an encrypted form to ensure data security, and each data provider also submits encrypted data indexes to enable queries over the encrypted data. We propose a novel Multi-Source Order-Preserving Symmetric Encryption (MOPSE) scheme whereby the cloud can merge the encrypted data indexes from multiple data providers without knowing the index content. MOPSE enables efficient and privacy-preserving query processing in that a data user can submit a single data query, the cloud can process over the encrypted data from all related data providers without knowing the query content. We also propose an enhanced scheme, MOPSE<sup>+</sup>, to more efficiently support the data queries by hierarchical data providers. Extensive analysis and experiments over real data sets demonstrate the efficacy and efficiency of MOPSE and MOPSE<sup>+</sup>.

Abstract licence: CC BY-NC-ND

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