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Ziller, A.* ; Mueller, T.T.* ; Braren, R.* ; Rueckert, D.* ; Kaissis, G.*

Privacy: An axiomatic approach.

Entropy 24:714 (2022)
Publ. Version/Full Text DOI PMC
Open Access Gold
Creative Commons Lizenzvertrag
The increasing prevalence of large-scale data collection in modern society represents a potential threat to individual privacy. Addressing this threat, for example through privacy-enhancing technologies (PETs), requires a rigorous definition of what exactly is being protected, that is, of privacy itself. In this work, we formulate an axiomatic definition of privacy based on quantifiable and irreducible information flows. Our definition synthesizes prior work from the domain of social science with a contemporary understanding of PETs such as differential privacy (DP). Our work highlights the fact that the inevitable difficulties of protecting privacy in practice are fundamentally information-theoretic. Moreover, it enables quantitative reasoning about PETs based on what they are protecting, thus fostering objective policy discourse about their societal implementation.
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Publication type Article: Journal article
Document type Scientific Article
Keywords Confidentiality ; Differential Privacy ; Information Flow ; Privacy ; Privacy-enhancing Technologies ; Secrecy
Language english
Publication Year 2022
HGF-reported in Year 2022
e-ISSN 1099-4300
Journal Entropy
Quellenangaben Volume: 24, Issue: 5, Pages: , Article Number: 714 Supplement: ,
Publisher MDPI
Reviewing status Peer reviewed
POF-Topic(s) 30205 - Bioengineering and Digital Health
Research field(s) Enabling and Novel Technologies
PSP Element(s) G-530014-001
Grants German Cancer Research Center
Deutsche Forschungsgemeinschaft
UK Research and Innovation
PubMed ID 35626597
Erfassungsdatum 2022-09-13