AIMS Medical Science (Dec 2017)

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
https://doi.org/10.3934/medsci.2018.1.1
Journal volume & issue
Vol. 5, no. 1
pp. 1 – 22

Abstract

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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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