Feedback-based integration of the whole process of data anonymization in a graphical interface

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Publication date
2019
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01A - Journal article
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Parent work
Algorithms
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DOI of the original publication
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Series
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Volume
12
Issue / Number
9
Pages / Duration
1-20
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Publisher / Publishing institution
MDPI
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Basel
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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.
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Subject (DDC)
330 - Wirtschaft
005 - Computer Programmierung, Programme und Daten
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ISBN
ISSN
1999-4893
Language
English
Created during FHNW affiliation
No
Strategic action fields FHNW
Publication status
Published
Review
Peer review of the complete publication
Open access category
Gold
License
'https://creativecommons.org/licenses/by/4.0/'
Citation
MEINDL, Bernhard und Matthias TEMPL, 2019. Feedback-based integration of the whole process of data anonymization in a graphical interface. Algorithms. 2019. Bd. 12, Nr. 9, S. 1–20. DOI 10.3390/a12090191. Verfügbar unter: https://doi.org/10.26041/fhnw-11055