A survey of state-of-the-art methods for securing medical databases

Andrei V. Kelarev; Xun Yi; Hui Cui; Leanne Rylands; Herbert F. Jelinek

doi:10.3934/medsci.2018.1.1

A survey of state-of-the-art methods for securing medical databases

Andrei V. Kelarev, Xun Yi, Hui Cui, Leanne Rylands, Herbert F. Jelinek

Research output: Contribution to journal › Article › Research › peer-review

Abstract

This review article presents a survey of recent work devoted to advanced state-of-the-art methods for securing of medical databases. We concentrate on three main directions, which have received attention recently: attribute-based encryption for enabling secure access to confidential medical databases distributed among several data centers; homomorphic encryption for providing answers to confidential queries in a secure manner; and privacy-preserving data mining used to analyze data stored in medical databases for verifying hypotheses and discovering trends. Only the most recent and significant work has been included.

Original language	English
Number of pages	22
Journal	AIMS Medical Science
Volume	5
Issue number	1
DOIs	https://doi.org/10.3934/medsci.2018.1.1
Publication status	Published - 2018
Externally published	Yes

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10.3934/medsci.2018.1.1

Cite this

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abstract = "This review article presents a survey of recent work devoted to advanced state-of-the-art methods for securing of medical databases. We concentrate on three main directions, which have received attention recently: attribute-based encryption for enabling secure access to confidential medical databases distributed among several data centers; homomorphic encryption for providing answers to confidential queries in a secure manner; and privacy-preserving data mining used to analyze data stored in medical databases for verifying hypotheses and discovering trends. Only the most recent and significant work has been included.",

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