Please use this identifier to cite or link to this item: https://doi.org/10.21256/zhaw-18250
Title: Feedback-based integration of the whole process of data anonymization in a graphical interface
Authors : Meindl, Bernhard
Templ, Matthias
et. al : No
Published in : Algorithms
Volume(Issue) : 12
Issue : 9
Pages : 191
Publisher / Ed. Institution : MDPI
Issue Date: 2019
License (according to publishing contract) : CC BY 4.0: Attribution 4.0 International
Type of review: Peer review (publication)
Language : English
Subjects : Anonymization; R-package; User interface; Feedback-system
Subject (DDC) : 005: Computer programming, programs and data
Abstract: The interactive, web-based point-and-click application presented in this article, allows anonymizing data without any knowledge in a programming language. Anonymization in data mining, but creating safe, anonymized data is by no means a trivial task. Both the methodological issues as well as know-how from subject matter specialists should be taken into account when anonymizing data. Even though specialized software such as sdcMicro exists, it is often difficult for nonexperts in a particular software and without programming skills to actually anonymize datasets without an appropriate app. The presented app is not restricted to apply disclosure limitation techniques but rather facilitates the entire anonymization process. This interface allows uploading data to the system, modifying them and to create an object defining the disclosure scenario. Once such a statistical disclosure control (SDC) problem has been defined, users can apply anonymization techniques to this object and get instant feedback on the impact on risk and data utility after SDC methods have been applied. Additional features, such as an Undo Button, the possibility to export the anonymized dataset or the required code for reproducibility reasons, as well its interactive features, make it convenient both for experts and nonexperts in R—the free software environment for statistical computing and graphics—to protect a dataset using this app.
Departement: School of Engineering
Organisational Unit: Institute of Data Analysis and Process Design (IDP)
Publication type: Article in scientific journal
DOI : 10.3390/a12090191
10.21256/zhaw-18250
ISSN: 1999-4893
URI: https://digitalcollection.zhaw.ch/handle/11475/18250
Appears in Collections:Publikationen School of Engineering

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