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Publikationstyp: Beitrag in wissenschaftlicher Zeitschrift
Art der Begutachtung: Peer review (Publikation)
Titel: A systematic overview on methods to protect sensitive data provided for various analyses
Autor/-in: Templ, Matthias
Sariyar, Murat
et. al: No
DOI: 10.1007/s10207-022-00607-5
10.21256/zhaw-26691
Erschienen in: International Journal of Information Security
Band(Heft): 21
Heft: 6
Seite(n): 1233
Seiten bis: 1246
Erscheinungsdatum: 2022
Verlag / Hrsg. Institution: Springer
ISSN: 1615-5262
1615-5270
Sprache: Englisch
Schlagwörter: Anonymization; Privacy-preserving computation; Federated learning; Synthetic data
Fachgebiet (DDC): 005: Computerprogrammierung, Programme und Daten
Zusammenfassung: In view of the various methodological developments regarding the protection of sensitive data, especially with respect to privacy-preserving computation and federated learning, a conceptual categorization and comparison between various methods stemming from different fields is often desired. More concretely, it is important to provide guidance for the practice, which lacks an overview over suitable approaches for certain scenarios, whether it is differential privacy for interactive queries, k-anonymity methods and synthetic data generation for data publishing, or secure federated analysis for multiparty computation without sharing the data itself. Here, we provide an overview based on central criteria describing a context for privacy-preserving data handling, which allows informed decisions in view of the many alternatives. Besides guiding the practice, this categorization of concepts and methods is destined as a step towards a comprehensive ontology for anonymization. We emphasize throughout the paper that there is no panacea and that context matters.
Weitere Angaben: Erworben im Rahmen der Schweizer Nationallizenzen (http://www.nationallizenzen.ch)
URI: https://digitalcollection.zhaw.ch/handle/11475/26691
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

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Templ, M., & Sariyar, M. (2022). A systematic overview on methods to protect sensitive data provided for various analyses. International Journal of Information Security, 21(6), 1233–1246. https://doi.org/10.1007/s10207-022-00607-5
Templ, M. and Sariyar, M. (2022) ‘A systematic overview on methods to protect sensitive data provided for various analyses’, International Journal of Information Security, 21(6), pp. 1233–1246. Available at: https://doi.org/10.1007/s10207-022-00607-5.
M. Templ and M. Sariyar, “A systematic overview on methods to protect sensitive data provided for various analyses,” International Journal of Information Security, vol. 21, no. 6, pp. 1233–1246, 2022, doi: 10.1007/s10207-022-00607-5.
TEMPL, Matthias und Murat SARIYAR, 2022. A systematic overview on methods to protect sensitive data provided for various analyses. International Journal of Information Security. 2022. Bd. 21, Nr. 6, S. 1233–1246. DOI 10.1007/s10207-022-00607-5
Templ, Matthias, and Murat Sariyar. 2022. “A Systematic Overview on Methods to Protect Sensitive Data Provided for Various Analyses.” International Journal of Information Security 21 (6): 1233–46. https://doi.org/10.1007/s10207-022-00607-5.
Templ, Matthias, and Murat Sariyar. “A Systematic Overview on Methods to Protect Sensitive Data Provided for Various Analyses.” International Journal of Information Security, vol. 21, no. 6, 2022, pp. 1233–46, https://doi.org/10.1007/s10207-022-00607-5.


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