Privacy Patterns for Pseudonymity - Archive ouverte HAL Access content directly
Book Sections Year : 2019

Privacy Patterns for Pseudonymity

(1) , (1)
1
Alexander Gabel
  • Function : Author
  • PersonId : 1036916
Ina Schiering
  • Function : Author
  • PersonId : 977002

Abstract

To implement the principle of Privacy by Design mentioned in the European General Data Protection Regulation one important measurement stated there is pseudonymisation. Pseudonymous data is widely used in medical applications and is investigated e.g. for vehicular ad-hoc networks and Smart Grid. The concepts used there address a broad range of important aspects and are therefore often specific and complex. Some privacy patterns are already addressing pseudonymity, but they are mostly abstract or rather very specific. This paper proposes privacy patterns for the development of pseudonymity concepts based on the analysis of pseudonymity solutions in use cases.
Fichier principal
Vignette du fichier
479119_1_En_11_Chapter.pdf (236.8 Ko) Télécharger le fichier
Origin : Files produced by the author(s)
Loading...

Dates and versions

hal-02271669 , version 1 (27-08-2019)

Licence

Attribution - CC BY 4.0

Identifiers

Cite

Alexander Gabel, Ina Schiering. Privacy Patterns for Pseudonymity. Eleni Kosta; Jo Pierson; Daniel Slamanig; Simone Fischer-Hübner; Stephan Krenn. Privacy and Identity Management. Fairness, Accountability, and Transparency in the Age of Big Data : 13th IFIP WG 9.2, 9.6/11.7, 11.6/SIG 9.2.2 International Summer School, Vienna, Austria, August 20-24, 2018, Revised Selected Papers, AICT-547, Springer International Publishing, pp.155-172, 2019, IFIP Advances in Information and Communication Technology, 978-3-030-16743-1. ⟨10.1007/978-3-030-16744-8_11⟩. ⟨hal-02271669⟩
81 View
30 Download

Altmetric

Share

Gmail Facebook Twitter LinkedIn More