@inproceedings{2e54153efc0348cba994a489a70a5a72,
title = "Statistical Disclosure Control when Publishing on Thematic Maps",
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.",
keywords = "Statistical disclosure control, privacy, Thematic maps, Cybersecurity",
author = "Douwe Hut and Jasper Goseling and {van Lieshout}, Marie-Colette and {de Wolf}, Peter-Paul and {de Jonge}, Edwin",
year = "2020",
doi = "10.1007/978-3-030-57521-2_14",
language = "English",
isbn = "978-3-030-57520-5",
series = "Lecture Notes in Computer Science",
publisher = "Springer",
pages = "195--205",
editor = "Josep Domingo-Ferrer and Krishnamurty Muralidhar",
booktitle = "Privacy in Statistical Databases",
address = "Germany",
note = "Privacy in Statistical Databases: UNESCO Chair in Data Privacy, International Conference, PSD 2020, PSD ; Conference date: 23-09-2020 Through 25-09-2020",
}