Privacy-Enhancing Technologies and Anonymisation in Light of GDPR and Machine Learning

Simone Fischer-Hübner, Marit Hansen, Jaap Henk Hoepman, Meiko Jensen*

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

188 Downloads (Pure)

Abstract

The use of Privacy-Enhancing Technologies in the field of data anonymisation and pseudonymisation raises a lot of questions with respect to legal compliance under GDPR and current international data protection legislation. Here, especially the use of innovative technologies based on machine learning may increase or decrease risks to data protection. A workshop held at the IFIP Summer School on Privacy and Identity Management showed the complexity of this field and the need for further interdisciplinary research on the basis of an improved joint understanding of legal and technical concepts.

Original languageEnglish
Title of host publicationPrivacy and Identity Management
Subtitle of host publication17th IFIP WG 9.2, 9.6/11.7, 11.6/SIG 9.2.2 International Summer School, Privacy and Identity 2022, Proceedings
EditorsFelix Bieker, Joachim Meyer, Sebastian Pape, Ina Schiering, Andreas Weich
PublisherSpringer Science and Business Media Deutschland GmbH
Pages11-20
Number of pages10
ISBN (Electronic)978-3-031-31971-6
ISBN (Print)978-3-031-31970-9, 978-3-031-31973-0
DOIs
Publication statusPublished - 2023
Event17th IFIP WG 9.2, 9.6/11.7, 11.6/SIG 9.2.2 International Summer School on Privacy and Identity Management, Privacy and Identity 2022 - Virtual, Online
Duration: 30-Aug-20222-Sept-2022

Publication series

NameIFIP Advances in Information and Communication Technology
Volume671 IFIP
ISSN (Print)1868-4238
ISSN (Electronic)1868-422X

Conference

Conference17th IFIP WG 9.2, 9.6/11.7, 11.6/SIG 9.2.2 International Summer School on Privacy and Identity Management, Privacy and Identity 2022
CityVirtual, Online
Period30/08/202202/09/2022

Fingerprint

Dive into the research topics of 'Privacy-Enhancing Technologies and Anonymisation in Light of GDPR and Machine Learning'. Together they form a unique fingerprint.

Cite this