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Secure search for encrypted personal health records from big data NoSQL databases in cloud

Version 2 2024-06-05, 05:31
Version 1 2023-10-24, 05:05
journal contribution
posted on 2024-06-05, 05:31 authored by L Chen, N Zhang, HM Sun, CC Chang, S Yu, KKR Choo
© 2019, Springer-Verlag GmbH Austria, part of Springer Nature. As the healthcare industry adopts the use of cloud to store personal health record (PHR), there is a need to ensure that we maintain the ability to perform efficient search on encrypted data (stored in the cloud). In this paper, we propose a secure searchable encryption scheme, which is designed to search on encrypted personal health records from a NoSQL database in semi-trusted cloud servers. The proposed scheme supports almost all query operations available in plaintext database environments, especially multi-dimensional, multi-keyword searches with range query. Specifically, in the proposed scheme, an Adelson-Velsky Landis (AVL) tree is utilized to construct the index, and an order-revealing encryption (ORE) algorithm is used to encrypt the AVL tree and realize range query. As document-based databases are probably the most popular NoSQL database, due to their flexibility, high efficiency, and ease of use, MongoDB, a document-based NoSQL database, is chosen to store the encrypted PHR data in our scheme. Experimental results show that the scheme can achieve secure and practical searchable encryption for PHRs. A comparison of the range query demonstrates that the time overhead of our ORE-based scheme is 25.5% shorter than that of the mOPE-based Arx (an encrypted database system) scheme.

History

Journal

Computing

ISSN

0010-485X

eISSN

1436-5057

Publication classification

C1 Refereed article in a scholarly journal

Publisher

Springer (part of Springer Nature)

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