Distributed privacy-preserving methods for statistical disclosure control

Javier Herranz, Jordi Nin, Vicenç Torra

Producción científica: Capítulo del libroContribución a congreso/conferenciarevisión exhaustiva

5 Citas (Scopus)

Resumen

Statistical disclosure control (SDC) methods aim to protect privacy of the confidential information included in some databases, for example by perturbing the non-confidential parts of the original databases. Such methods are commonly used by statistical agencies before publishing the perturbed data, which must ensure privacy at the same time as it preserves as much as possible the statistical information of the original data. In this paper we consider the problem of designing distributed privacy-preserving versions of these perturbation methods: each part of the original database is owned by a different entity, and they want to jointly compute the perturbed version of the global database, without leaking any sensitive information on their individual parts of the original data. We show that some perturbation methods do not allow a private distributed extension, whereas other methods do. Among the methods that allow a distributed privacy-preserving version, we can list noise addition, resampling and a new protection method, rank shuffling, which is described and analyzed here for the first time.

Idioma originalInglés
Título de la publicación alojadaData Privacy Management and Autonomous Spontaneous Security - 4th International Workshop, DPM 2009, and Second International Workshop, SETOP 2009, Revised Selected Papers
Páginas33-47
Número de páginas15
DOI
EstadoPublicada - 2010
Publicado de forma externa
Evento4th International Workshop on Data Privacy Management, DPM 2009, and 2nd International Workshop on Autonomous and Spontaneous Security, SETOP 2009 - St. Malo, Francia
Duración: 24 sept 200925 sept 2009

Serie de la publicación

NombreLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volumen5939 LNCS
ISSN (versión impresa)0302-9743
ISSN (versión digital)1611-3349

Conferencia

Conferencia4th International Workshop on Data Privacy Management, DPM 2009, and 2nd International Workshop on Autonomous and Spontaneous Security, SETOP 2009
País/TerritorioFrancia
CiudadSt. Malo
Período24/09/0925/09/09

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