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ThinkMind // ICDS 2020, The Fourteenth International Conference on Digital Society // View article icds_2020_1_20_18004


A Framework for a User-friendly Statistical Disclosure Control Tool

Authors:
Anshika Rawat
Mortaza S. Bargh
Afshin Amighi
Marijn Janssen

Keywords: Statistical Disclosure Control; Data Protection

Abstract:
Public organisations are opening more and more data to increase their transparency. But more often than not, data cannot be opened without modification due to data protection issues. There are Statistical Disclosure Control (SDC) tools that can help to accomplish this. However, these tools are not intuitive for end-users, especially for those who are not deeply familiar with data science. The end-users are mostly public servants who want to open data. Therefore, the main objective of this paper is to develop a framework for a user-friendly tool based on data disclosure methods and usability guidelines for protecting microdata. The developed framework can be used to design and evaluate a tool that can be used by data controllers within the Dutch governmental institutions for anonymising data. This contributes to the sharing of more data with the public or between organisations with a minimised risk of disclosing the identity of the individuals the data is about.

Pages: 7 to 11

Copyright: Copyright (c) IARIA, 2020

Publication date: March 22, 2020

Published in: conference

ISSN: 2308-3956

ISBN: 978-1-61208-760-3

Location: Valencia, Spain

Dates: from November 21, 2020 to November 25, 2020

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