A FORMALIZATION OF RECORD LINKAGE AND ITS APPLICATION TO DATA PROTECTION

被引:3
|
作者
Torra, Vicenc [1 ]
Stokes, Klara [2 ]
机构
[1] CSIC, Inst Invest Intel Ligencia Artificial, IIIA, Bellaterra 08193, Spain
[2] Univ Oberta Catalunya, Internet Interdisciplinary Inst IN3, Barcelona 08018, Catalonia, Spain
关键词
Re-identificationl; record linkage; k-anonymity; belief functions; DISCLOSURE RISK; K-ANONYMITY; REIDENTIFICATION; MODEL;
D O I
10.1142/S0218488512400302
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Re-identification and record linkage are tools used to measure disclosure risk in data privacy. Given two data files, record linkage establishes links between those records that correspond to the same individual. These links are often expressed in terms of probability distributions. This paper presents a review of a formalization of re-identification in terms of compatible belief functions. This formalization makes it possible to define the set of methods for re-identification that are relevant for the estimation of disclosure risk in privacy protection. Any re-identification method that does not fulfill the criteria for being in this set, may be discarded in a theoretical disclosure risk analysis. The focus in this paper is on providing examples of how this formalization can be applied in a few different scenarios in data privacy.
引用
收藏
页码:907 / 919
页数:13
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