Estimating Re-identification Risk by Means of Formal Conceptualization

被引：1

作者：

Aranda-Corral, Gonzalo A. ^{[1
]}

Borrego-Diaz, Joaquin ^{[2
]}

Galan-Paez, Juan ^{[2
]}

机构：

[1] Univ Huelva, Dept Informat Technol, Huelva, Spain

[2] Univ Seville, Dept Comp Sci & Artificial Intelligence, Seville, Spain

来源：

14TH INTERNATIONAL CONFERENCE ON COMPUTATIONAL INTELLIGENCE IN SECURITY FOR INFORMATION SYSTEMS AND 12TH INTERNATIONAL CONFERENCE ON EUROPEAN TRANSNATIONAL EDUCATIONAL (CISIS 2021 AND ICEUTE 2021) | 2022年 / 1400卷

关键词：

Privacy; Re-identification; Formal concept analysis; Risk metrics;

D O I：

10.1007/978-3-030-87872-6_2

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Risk-based methodologies for de-identification provide solutions to ensure privacy. These are based on the availability of sound metrics to estimate the risk of re-identification. Two issues associated with classical risk estimation are, on the one hand, the adequacy of the metric and, on the other hand, its static nature -that is, any change in the database to reduce the risk could imply recomputing the metrics, for example, by removing compromised data (data with a high probability of re-identification). This paper presents a semantic-based risk estimation -by means of Formal Concept Analysis- that allows to estimate a priori the risk of compromised data deletion.

引用

页码：13 / 22

页数：10

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