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

Contributor(s): Material type: TextSeries: Information Systems and Applications, incl. Internet/Web, and HCI ; 12276Publisher: Cham : Springer International Publishing : Imprint: Springer, 2020Edition: 1st ed. 2020Description: 1 online resource (XI, 370 p. 25 illus.)Content type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9783030575212
Subject(s): Additional physical formats: Printed edition:: No title; Printed edition:: No titleDDC classification:
  • 006.312 23
LOC classification:
  • QA76.9.D343
Online resources:
Contents:
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.
In: Springer Nature eBookSummary: 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.
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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.

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.

Print version record.

Licensed e-book