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Open AccessArticle

Feedback-Based Integration of the Whole Process of Data Anonymization in a Graphical Interface

1
Methods Unit, Statistics Austria, 1110 Vienna, Austria
2
Institute for Data Analysis and Process Design, Zurich University of Applied Sciences, 8400 Winterthur, Switzerland
*
Author to whom correspondence should be addressed.
Algorithms 2019, 12(9), 191; https://doi.org/10.3390/a12090191
Received: 23 July 2019 / Revised: 5 September 2019 / Accepted: 5 September 2019 / Published: 10 September 2019
(This article belongs to the Special Issue Statistical Disclosure Control for Microdata)
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.
Keywords: anonymization; R-package; user interface; feedback-system anonymization; R-package; user interface; feedback-system
MDPI and ACS Style

Meindl, B.; Templ, M. Feedback-Based Integration of the Whole Process of Data Anonymization in a Graphical Interface. Algorithms 2019, 12, 191.

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