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A data-sharing scheme that supports multi-keyword search for electronic medical records

As cloud storage technology develops, data sharing of cloud-based electronic medical records (EMRs) has become a hot topic in the academia and healthcare sectors. To solve the problem of secure search and sharing of EMR in cloud platforms, an EMR data-sharing scheme supporting multi-keyword search i...

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Detalles Bibliográficos
Autores principales: Niu, Shufen, Liu, Wenke, Han, Song, Fang, Lizhi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7790426/
https://www.ncbi.nlm.nih.gov/pubmed/33411842
http://dx.doi.org/10.1371/journal.pone.0244979
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author Niu, Shufen
Liu, Wenke
Han, Song
Fang, Lizhi
author_facet Niu, Shufen
Liu, Wenke
Han, Song
Fang, Lizhi
author_sort Niu, Shufen
collection PubMed
description As cloud storage technology develops, data sharing of cloud-based electronic medical records (EMRs) has become a hot topic in the academia and healthcare sectors. To solve the problem of secure search and sharing of EMR in cloud platforms, an EMR data-sharing scheme supporting multi-keyword search is proposed. The proposed scheme combines searchable encryption and proxy re-encryption technologies to perform keyword search and achieve secure sharing of encrypted EMR. At the same time, the scheme uses a traceable pseudo identity to protect the patient’s private information. Our scheme is proven secure based on the modified Bilinear Diffie-Hellman assumption and Quotient Decisional Bilinear Diffie-Hellman assumption under the random oracle model. The performance of our scheme is evaluated through theoretical analysis and numerical simulation.
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spelling pubmed-77904262021-01-27 A data-sharing scheme that supports multi-keyword search for electronic medical records Niu, Shufen Liu, Wenke Han, Song Fang, Lizhi PLoS One Research Article As cloud storage technology develops, data sharing of cloud-based electronic medical records (EMRs) has become a hot topic in the academia and healthcare sectors. To solve the problem of secure search and sharing of EMR in cloud platforms, an EMR data-sharing scheme supporting multi-keyword search is proposed. The proposed scheme combines searchable encryption and proxy re-encryption technologies to perform keyword search and achieve secure sharing of encrypted EMR. At the same time, the scheme uses a traceable pseudo identity to protect the patient’s private information. Our scheme is proven secure based on the modified Bilinear Diffie-Hellman assumption and Quotient Decisional Bilinear Diffie-Hellman assumption under the random oracle model. The performance of our scheme is evaluated through theoretical analysis and numerical simulation. Public Library of Science 2021-01-07 /pmc/articles/PMC7790426/ /pubmed/33411842 http://dx.doi.org/10.1371/journal.pone.0244979 Text en © 2021 Niu et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Niu, Shufen
Liu, Wenke
Han, Song
Fang, Lizhi
A data-sharing scheme that supports multi-keyword search for electronic medical records
title A data-sharing scheme that supports multi-keyword search for electronic medical records
title_full A data-sharing scheme that supports multi-keyword search for electronic medical records
title_fullStr A data-sharing scheme that supports multi-keyword search for electronic medical records
title_full_unstemmed A data-sharing scheme that supports multi-keyword search for electronic medical records
title_short A data-sharing scheme that supports multi-keyword search for electronic medical records
title_sort data-sharing scheme that supports multi-keyword search for electronic medical records
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7790426/
https://www.ncbi.nlm.nih.gov/pubmed/33411842
http://dx.doi.org/10.1371/journal.pone.0244979
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