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

AIMS Medical Science

article

Andrei V. Kelarev¹  Xun Yi¹  Hui Cui¹  Leanne Rylands²  Herbert F. Jelinek¹ 

[1] School of Science, RMIT University;School of Computing, Engineering and Mathematics, Western Sydney University;Center for Research in Complex Systems and School of Community Health, Charles Sturt University

关键词: medical databases;    privacy and security;    attribute-based encryption;    homomorphic encryption;    privacy preserving data mining;    ;   

DOI  :  10.3934/medsci.2018.1.1

来源: American Institute of Mathematical Sciences

【 摘 要 】

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.

【 授权许可】

CC BY