Privacy in Statistical Databases : UNESCO Chair in Data Privacy, International Conference, PSD 2020, Tarragona, Spain, September 23–25, 2020, Proceedings / edited by Josep Domingo-Ferrer, Krishnamurty Muralidhar

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Resource type: Ressourcentyp: Buch (Online)Book (Online)Language: English Series: Information Systems and Applications, incl. Internet/Web, and HCI ; 12276 | Springer eBook CollectionPublisher: Cham : Springer International Publishing, 2020Publisher: Cham : Imprint: Springer, 2020Edition: 1st ed. 2020Description: 1 Online-Ressource(XI, 370 p. 25 illus.)ISBN:

9783030575212

Subject(s):

Additional physical formats: 9783030575205 | 9783030575229 | Erscheint auch als: 9783030575205 Druck-Ausgabe | Erscheint auch als: 9783030575229 Druck-AusgabeDDC classification:

006.312 23

DOI: DOI: 10.1007/978-3-030-57521-2Online resources:

Summary: Privacy models -- Microdata protection -- Protection of statistical tables -- Protection of interactive and mobility databases -- Record linkage and alternative methods -- Synthetic data -- Data quality -- Case studies.Summary: The Chapter “Explaining recurrent machine learning models: integral privacy revisited” is available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.PPN: PPN: 1734627344Package identifier: Produktsigel: ZDB-2-LNC | ZDB-2-SCS | ZDB-2-SXCS | ZDB-2-SEB

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