Statistical Disclosure Control when Publishing on Thematic Maps

Douwe Hut, Jasper Goseling, Marie-Colette van Lieshout, Peter-Paul de Wolf, Edwin de Jonge

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

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Abstract

The spatial distribution of a variable, such as the energy consumption per company, is usually plotted by colouring regions of the study area according to an underlying table which is already protected from disclosing sensitive information. The result is often heavily influenced by the shape and size of the regions. In this paper, we are interested in producing a continuous plot of the variable directly from microdata and we protect it by adding random noise. We consider a simple attacker scenario and develop an appropriate sensitivity rule that can be used to determine the amount of noise needed to protect the plot from disclosing private information.
Original languageEnglish
Title of host publicationPrivacy in Statistical Databases
Subtitle of host publicationUNESCO Chair in Data Privacy, International Conference, PSD 2020, Tarragona, Spain, September 23–25, 2020, Proceedings
EditorsJosep Domingo-Ferrer, Krishnamurty Muralidhar
Place of PublicationCham
PublisherSpringer
Pages195-205
ISBN (Electronic)978-3-030-57521-2
ISBN (Print)978-3-030-57520-5
DOIs
Publication statusPublished - 2020
EventPrivacy in Statistical Databases: UNESCO Chair in Data Privacy, International Conference, PSD 2020 - Tarragona, Spain
Duration: 23 Sep 202025 Sep 2020

Publication series

NameLecture Notes in Computer Science
PublisherSpringer
Volume12276
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

ConferencePrivacy in Statistical Databases: UNESCO Chair in Data Privacy, International Conference, PSD 2020
Abbreviated titlePSD
CountrySpain
CityTarragona
Period23/09/2025/09/20

Keywords

  • Statistical disclosure control
  • privacy
  • Thematic maps
  • Cybersecurity

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