Articles producció científica> Enginyeria Informàtica i Matemàtiques

Individual differential privacy: A utility-preserving formulation of differential privacy guarantees

  • Datos identificativos

    Identificador: PC:2711
    Handle: http://hdl.handle.net/20.500.11797/PC2711
  • Autores:

    Soria-Comas, J.
    Domingo-Ferrer, J.
    Sanchez, D.
    Megias, D.
  • Otros:

    Autor según el artículo: Soria-Comas, J.; Domingo-Ferrer, J.; Sanchez, D.; Megias, D.
    Departamento: Enginyeria Informàtica i Matemàtiques
    Autor/es de la URV: SORIA COMAS, JORGE; DOMINGO FERRER, JOSEP; Sanchez, D.; Megias, D.
    Palabras clave: Data privacy Data utility Differential privacy
    Resumen: Differential privacy is a popular privacy model within the research community because of the strong privacy guarantee it offers, namely that the presence or absence of any individual in a data set does not significantly influence the results of analyses on the data set. However, enforcing this strict guarantee in practice significantly distorts data and/or limits data uses, thus diminishing the analytical utility of the differentially private results. In an attempt to address this shortcoming, several relaxations of differential privacy have been proposed that trade off privacy guarantees for improved data utility. In this paper, we argue that the standard formalization of differential privacy is stricter than required by the intuitive privacy guarantee it seeks. In particular, the standard formalization requires indistinguishability of results between any pair of neighbor data sets, while indistinguishability between the actual data set and its neighbor data sets should be enough. This limits the data controller's ability to adjust the level of protection to the actual data, hence resulting in significant accuracy loss. In this respect, we propose individual differential privacy, an alternative differential privacy notion that offers the same privacy guarantees as standard differential privacy to individuals (even though not to groups of individuals). This new notion allows the data controller to adjust the distortion to the actual data set, which results in less distortion and more analytical accuracy. We propose several mechanisms to attain individual differential privacy and we compare the new notion against standard differential privacy in terms of the accuracy of the analytical results.
    Grupo de investigación: Seguretat i Privadesa
    Áreas temáticas: Enginyeria informàtica Ingeniería informática Computer engineering
    Acceso a la licencia de uso: https://creativecommons.org/licenses/by/3.0/es/
    ISSN: 1556-6013
    Identificador del autor: ; ; 0000-0001-7275-7887; 0000-0002-0507-7731
    Fecha de alta del registro: 2017-04-04
    Página final: 1429
    Volumen de revista: 12
    Versión del articulo depositado: info:eu-repo/semantics/submittedVersion
    Enlace a la fuente original: http://ieeexplore.ieee.org/document/7839941/
    DOI del artículo: 10.1109/TIFS.2017.2663337
    Entidad: Universitat Rovira i Virgili
    Año de publicación de la revista: 2017
    Página inicial: 1418
    Tipo de publicación: Article Artículo Article
  • Palabras clave:

    Seguretat informàtica
    Protecció de dades
    Data privacy
    Data utility
    Differential privacy
    Enginyeria informàtica
    Ingeniería informática
    Computer engineering
    1556-6013
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