Efficient Search Over Encrypted Medical Data With Known-Plaintext/Background Models and Unlinkability

In advanced health care systems, patients’ medical data can be outsourced to cloud servers to enable remote healthcare service providers to access and analyze patients’ data from any location to provide better treatment. However, outsourcing sensitive medical data makes data ow...

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Autores principales:	Sherif Abdelfattah, Mohamed Baza, Mahmoud M. Badr, Mohamed M. E. A. Mahmoud, Gautam Srivastava, Fawaz Alsolami, Abdullah Marish Ali
Formato:	article
Lenguaje:	EN
Publicado:	IEEE 2021
Materias:	Security privacy e-health searchable encryption schemes cloud computing Electrical engineering. Electronics. Nuclear engineering TK1-9971
Acceso en línea:	https://doaj.org/article/f2964b19947b4c09b12b0e53d0661812
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spelling	oai:doaj.org-article:f2964b19947b4c09b12b0e53d06618122021-11-17T00:00:34ZEfficient Search Over Encrypted Medical Data With Known-Plaintext/Background Models and Unlinkability2169-353610.1109/ACCESS.2021.3126200https://doaj.org/article/f2964b19947b4c09b12b0e53d06618122021-01-01T00:00:00Zhttps://ieeexplore.ieee.org/document/9605644/https://doaj.org/toc/2169-3536In advanced health care systems, patients’ medical data can be outsourced to cloud servers to enable remote healthcare service providers to access and analyze patients’ data from any location to provide better treatment. However, outsourcing sensitive medical data makes data owners, i.e., patients, concerned about their privacy because private companies run the cloud service and the data can be accessed by them. Therefore, it is important to encrypt the data in the form of documents before outsourcing them to the cloud in a way that enables a data user, i.e., a doctor, to search over these documents without allowing the cloud provider to learn any private information about patients. Several schemes have been proposed to enable search over encrypted medical cloud data to preserve patient privacy, but the existing schemes suffer from high communication/computation overhead because they are designed for a single-data-owner setting. Moreover, they are not secure against known-plaintext/background and linkability attacks and do not allow doctors to customize their search to avoid downloading irrelevant documents. In this paper, we develop an efficient search scheme over encrypted data for a multi-data-owner setting. To secure our scheme, the cloud server obtains noisy similarity scores and doctors de-noise them to download the most relevant documents. Our scheme enables doctors to prescribe search conditions to customize the search without revealing the conditions to the server. Our formal proof and analysis indicate that our scheme can preserve privacy and is secure against known-plaintext/background and linkability attacks, and the results of extensive experiments demonstrate the efficiency of our scheme compared to the existing works.Sherif AbdelfattahMohamed BazaMahmoud M. BadrMohamed M. E. A. MahmoudGautam SrivastavaFawaz AlsolamiAbdullah Marish AliIEEEarticleSecurityprivacye-healthsearchable encryption schemescloud computingElectrical engineering. Electronics. Nuclear engineeringTK1-9971ENIEEE Access, Vol 9, Pp 151129-151141 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Security privacy e-health searchable encryption schemes cloud computing Electrical engineering. Electronics. Nuclear engineering TK1-9971
spellingShingle	Security privacy e-health searchable encryption schemes cloud computing Electrical engineering. Electronics. Nuclear engineering TK1-9971 Sherif Abdelfattah Mohamed Baza Mahmoud M. Badr Mohamed M. E. A. Mahmoud Gautam Srivastava Fawaz Alsolami Abdullah Marish Ali Efficient Search Over Encrypted Medical Data With Known-Plaintext/Background Models and Unlinkability
description	In advanced health care systems, patients’ medical data can be outsourced to cloud servers to enable remote healthcare service providers to access and analyze patients’ data from any location to provide better treatment. However, outsourcing sensitive medical data makes data owners, i.e., patients, concerned about their privacy because private companies run the cloud service and the data can be accessed by them. Therefore, it is important to encrypt the data in the form of documents before outsourcing them to the cloud in a way that enables a data user, i.e., a doctor, to search over these documents without allowing the cloud provider to learn any private information about patients. Several schemes have been proposed to enable search over encrypted medical cloud data to preserve patient privacy, but the existing schemes suffer from high communication/computation overhead because they are designed for a single-data-owner setting. Moreover, they are not secure against known-plaintext/background and linkability attacks and do not allow doctors to customize their search to avoid downloading irrelevant documents. In this paper, we develop an efficient search scheme over encrypted data for a multi-data-owner setting. To secure our scheme, the cloud server obtains noisy similarity scores and doctors de-noise them to download the most relevant documents. Our scheme enables doctors to prescribe search conditions to customize the search without revealing the conditions to the server. Our formal proof and analysis indicate that our scheme can preserve privacy and is secure against known-plaintext/background and linkability attacks, and the results of extensive experiments demonstrate the efficiency of our scheme compared to the existing works.
format	article
author	Sherif Abdelfattah Mohamed Baza Mahmoud M. Badr Mohamed M. E. A. Mahmoud Gautam Srivastava Fawaz Alsolami Abdullah Marish Ali
author_facet	Sherif Abdelfattah Mohamed Baza Mahmoud M. Badr Mohamed M. E. A. Mahmoud Gautam Srivastava Fawaz Alsolami Abdullah Marish Ali
author_sort	Sherif Abdelfattah
title	Efficient Search Over Encrypted Medical Data With Known-Plaintext/Background Models and Unlinkability
title_short	Efficient Search Over Encrypted Medical Data With Known-Plaintext/Background Models and Unlinkability
title_full	Efficient Search Over Encrypted Medical Data With Known-Plaintext/Background Models and Unlinkability
title_fullStr	Efficient Search Over Encrypted Medical Data With Known-Plaintext/Background Models and Unlinkability
title_full_unstemmed	Efficient Search Over Encrypted Medical Data With Known-Plaintext/Background Models and Unlinkability
title_sort	efficient search over encrypted medical data with known-plaintext/background models and unlinkability
publisher	IEEE
publishDate	2021
url	https://doaj.org/article/f2964b19947b4c09b12b0e53d0661812
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Efficient Search Over Encrypted Medical Data With Known-Plaintext/Background Models and Unlinkability

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