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 journalArticleResearchpeer-review


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 languageEnglish
Number of pages22
JournalAIMS Medical Science
Issue number1
Publication statusPublished - 2018
Externally publishedYes

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