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Privacy Evaluation Protocols for the Evaluation of Soft-Biometric Privacy-Enhancing Technologies
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Datum
2020
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Gesellschaft für Informatik e.V.
Zusammenfassung
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.