Articles producció científica> Enginyeria Informàtica i Matemàtiques

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

  • Dades identificatives

    Identificador: PC:2711
    Autors:
    Soria-Comas, J.Domingo-Ferrer, J.Sanchez, D.Megias, D.
    Resum:
    DOI: 10.1109/TIFS.2017.2663337 URL: http://ieeexplore.ieee.org/document/7839941/ Filiació URV: SI Info.add.: Article number 7839941
  • Altres:

    Autor segons l'article: Soria-Comas, J.; Domingo-Ferrer, J.; Sanchez, D.; Megias, D.
    Departament: Enginyeria Informàtica i Matemàtiques
    Autor/s de la URV: SORIA COMAS, JORGE; DOMINGO FERRER, JOSEP; Sanchez, D.; Megias, D.
    Paraules clau: Data privacy Data utility Differential privacy
    Resum: 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.
    Grup de recerca: Seguretat i Privadesa
    Àrees temàtiques: Enginyeria informàtica Ingeniería informática Computer engineering
    Accès a la llicència d'ús: https://creativecommons.org/licenses/by/3.0/es/
    ISSN: 1556-6013
    Identificador de l'autor: ; ; 0000-0001-7275-7887; 0000-0002-0507-7731
    Data d'alta del registre: 2017-04-04
    Pàgina final: 1429
    Volum de revista: 12
    Versió de l'article dipositat: info:eu-repo/semantics/submittedVersion
    Enllaç font original: http://ieeexplore.ieee.org/document/7839941/
    URL Document de llicència: https://repositori.urv.cat/ca/proteccio-de-dades/
    DOI de l'article: 10.1109/TIFS.2017.2663337
    Entitat: Universitat Rovira i Virgili
    Any de publicació de la revista: 2017
    Pàgina inicial: 1418
    Tipus de publicació: Article Artículo Article
  • Paraules clau:

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

  • Cerca a google

    Search to google scholar