Privacy: An Axiomatic Approach

Alexander Ziller, Tamara T. Mueller, Rickmer Braren, Daniel Rueckert, Georgios Kaissis

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

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.

Original languageEnglish
Article number714
JournalEntropy
Volume24
Issue number5
DOIs
StatePublished - May 2022

Keywords

  • confidentiality
  • differential privacy
  • information flow
  • privacy
  • privacy-enhancing technologies
  • secrecy

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