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https://doi.org/10.21256/zhaw-18250| Publikationstyp: | Beitrag in wissenschaftlicher Zeitschrift |
| Art der Begutachtung: | Peer review (Publikation) |
| Titel: | Feedback-based integration of the whole process of data anonymization in a graphical interface |
| Autor/-in: | Meindl, Bernhard Templ, Matthias |
| et. al: | No |
| DOI: | 10.3390/a12090191 10.21256/zhaw-18250 |
| Erschienen in: | Algorithms |
| Band(Heft): | 12 |
| Heft: | 9 |
| Seite(n): | 191 |
| Erscheinungsdatum: | 2019 |
| Verlag / Hrsg. Institution: | MDPI |
| ISSN: | 1999-4893 |
| Sprache: | Englisch |
| Schlagwörter: | Anonymization; R-package; User interface; Feedback-system |
| Fachgebiet (DDC): | 005: Computerprogrammierung, Programme und Daten |
| Zusammenfassung: | 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. |
| URI: | https://digitalcollection.zhaw.ch/handle/11475/18250 |
| Volltext Version: | Publizierte Version |
| Lizenz (gemäss Verlagsvertrag): | CC BY 4.0: Namensnennung 4.0 International |
| Departement: | School of Engineering |
| Organisationseinheit: | Institut für Datenanalyse und Prozessdesign (IDP) |
| Enthalten in den Sammlungen: | Publikationen School of Engineering |
Dateien zu dieser Ressource:
| Datei | Beschreibung | Größe | Format | |
|---|---|---|---|---|
| algorithms-12-00191-v2.pdf | 876.8 kB | Adobe PDF |  Öffnen/Anzeigen |
Zur Langanzeige
Meindl, B., & Templ, M. (2019). Feedback-based integration of the whole process of data anonymization in a graphical interface. Algorithms, 12(9), 191. https://doi.org/10.3390/a12090191
Meindl, B. and Templ, M. (2019) ‘Feedback-based integration of the whole process of data anonymization in a graphical interface’, Algorithms, 12(9), p. 191. Available at: https://doi.org/10.3390/a12090191.
B. Meindl and M. Templ, “Feedback-based integration of the whole process of data anonymization in a graphical interface,” Algorithms, vol. 12, no. 9, p. 191, 2019, doi: 10.3390/a12090191.
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. 191. DOI 10.3390/a12090191
Meindl, Bernhard, and Matthias Templ. 2019. “Feedback-Based Integration of the Whole Process of Data Anonymization in a Graphical Interface.” Algorithms 12 (9): 191. https://doi.org/10.3390/a12090191.
Meindl, Bernhard, and Matthias Templ. “Feedback-Based Integration of the Whole Process of Data Anonymization in a Graphical Interface.” Algorithms, vol. 12, no. 9, 2019, p. 191, https://doi.org/10.3390/a12090191.
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