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Computing
Erschienen in: Computing 6/2020

01.10.2019

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

verfasst von: Lanxiang Chen, Nan Zhang, Hung-Min Sun, Chin-Chen Chang, Shui Yu, Kim-Kwang Raymond Choo

Erschienen in: Computing | Ausgabe 6/2020

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Abstract

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.
Vorheriger Artikel Feature selection and evaluation for software usability model using modified moth-flame optimization
Nächster Artikel Implementation of an energy saving cloud infrastructure with virtual machine power usage monitoring and live migration on OpenStack

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Metadaten
Titel
Secure search for encrypted personal health records from big data NoSQL databases in cloud
verfasst von
Lanxiang Chen
Nan Zhang
Hung-Min Sun
Chin-Chen Chang
Shui Yu
Kim-Kwang Raymond Choo
Publikationsdatum
01.10.2019
Verlag
Springer Vienna
Erschienen in
Computing / Ausgabe 6/2020
Print ISSN: 0010-485X
Elektronische ISSN: 1436-5057
DOI
https://doi.org/10.1007/s00607-019-00762-z

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