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Privacy Evaluation Protocols for the Evaluation of Soft-Biometric Privacy-Enhancing Technologies

: Terhörst, Philipp; Huber, Marco; Damer, Naser; Rot, Peter; Kirchbuchner, Florian; Struc, Vitomir; Kuijper, Arjan

Brömme, Arslan (Ed.) ; Gesellschaft für Informatik -GI-, Bonn:
BIOSIG 2020, 19th International Conference of the Biometrics Special Interest Group. Proceedings : 16.-18.09.2020, Fully Virtual Conference
Bonn: GI, 2020 (GI-Edition - Lecture Notes in Informatics (LNI). Proceedings P-306)
ISBN: 978-3-88579-700-5
Gesellschaft für Informatik, Special Interest Group on Biometrics and Electronic Signatures (BIOSIG International Conference) <19, 2020, Online>
Bundesministerium für Bildung und Forschung BMBF (Deutschland)
Fraunhofer IGD ()
Lead Topic: Smart City; Lead Topic: Visual Computing as a Service; Research Line: Computer vision (CV); Research Line: Human computer interaction (HCI); biometric; face recognition; privacy enhancing technologies; evaluation scheme; machine learning; CRISP; ATHENE

Biometric data includes privacy-sensitive information, such as soft-biometrics. Soft-biometric privacy enhancing technologies aim at limiting the possibility of deducing such information. Previous works proposed several solutions to this problem using several different evaluation processes, metrics, and attack scenarios. The absence of a standardized evaluation protocol makes a meaningful comparison of these solutions difficult. In this work, we propose privacy evaluation protocols (PEPs) for privacy-enhancing technologies (PETs) dealing with soft-biometric privacy. Our framework evaluates PETs in the most critical scenario of an attacker that knows and adapts to the systems privacy-mechanism. Moreover, our PEPs differentiate between PET of learning-based or training-free nature. To ensure that our protocol meets the highest standards in both cases, it is based on Kerckhoffs‘s principle of cryptography.