Privacy-preserving record linkage

被引:2
|
作者
Verykios, Vassilios S. [1 ]
Christen, Peter [2 ]
机构
[1] Hellen Open Univ, Sch Sci & Technol, Patras, Greece
[2] Australian Natl Univ, Res Sch Comp Sci, Coll Engn & Comp Sci, Canberra, ACT, Australia
关键词
SECURITY;
D O I
10.1002/widm.1101
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
It has been recognized that sharing data between organizations can be of great benefit, since it can help discover novel and valuable information that is not available in individual databases. However, as organizations are under pressure to better utilize their large databases through sharing, integration, and analysis, protecting the privacy of personal information in such databases is an increasingly difficult task. Record linkage is the task of identifying and matching records that correspond to the same real-world entity in several databases. This task implies a crucial infrastructure component in many modern information systems. Privacy and confidentiality concerns, however, commonly prevent the matching of databases that contain personal information across different organizations. In the past decade, efforts in the research area of privacy-preserving record linkage (PPRL) have aimed to develop techniques that facilitate the matching of records across databases such that besides the matched records no private or confidential information is being revealed to any organisztion involved in such a linkage, or to any external party. We discuss the development of key techniques that solve the three main subproblems of PPRL, namely privacy, linkage quality, and scaling PPRL to large databases. We then highlight open challenges in this research area. (C) 2013 Wiley Periodicals, Inc.
引用
收藏
页码:321 / 332
页数:12
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