Application-Oriented Selection of Privacy Enhancing Technologies
2022,
Kunz, Immanuel,
Binder, Andreas Maria
To create privacy-friendly software designs, architects need comprehensive knowledge of privacy-enhancing technologies (PETs) and their properties. Existing works that systemize PETs, however, are outdated or focus on comparison criteria rather than providing guidance for their practical selection. In this short paper we present an enhanced classification of PETs that is more application-oriented than previous proposals. It integrates existing criteria like the privacy protection goal, and also considers practical criteria like the functional context, a technology’s maturity, and its impact on various non-functional requirements.
