• DocumentCode
    182001
  • Title

    Privacy Dashboards: Reconciling Data-Driven Business Models and Privacy

  • Author

    Zimmermann, Christian ; Accorsi, Rafael ; Muller, Gunter

  • Author_Institution
    Bus. Process Security Group, Univ. of Freiburg, Freiburg, Germany
  • fYear
    2014
  • fDate
    8-12 Sept. 2014
  • Firstpage
    152
  • Lastpage
    157
  • Abstract
    We argue for the use of Privacy Dashboards as enablers for privacy-enabled data-driven business models. Specifically, while dashboards are succesful instruments in business intelligence tools, their use in privacy protection is far less well-understood. Addressing this problem at the technical level, this paper provides a classification scheme for Privacy Dashboards and elaborates on the current state of the art to draw a research agenda for designing Privacy Dashboards that cater to users´ desire of control and businesses´ need for data collection and usage.
  • Keywords
    business data processing; data acquisition; data protection; pattern classification; business intelligence tools; classification scheme; data collection; data usage; privacy dashboards; privacy protection; privacy-enabled data-driven business models; Accuracy; Business; Data collection; Data privacy; Google; Instruments; Privacy;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Availability, Reliability and Security (ARES), 2014 Ninth International Conference on
  • Conference_Location
    Fribourg
  • Type

    conf

  • DOI
    10.1109/ARES.2014.27
  • Filename
    6980276