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

Terhorst, Philipp and Huber, Marco and Damer, Naser and Rot, Peter and Kirchbuchner, Florian and Struc, Vitomir and Kuijper, Arjan (2020):
Privacy Evaluation Protocols for the Evaluation of Soft-Biometric Privacy-Enhancing Technologies.
pp. 215-222, 19th International Conference of the Biometrics Special Interest Group (BIOSIG 2020), virtual Conference, 16.-18.09., ISBN 978-3-88579-700-5,
[Conference or Workshop Item]

Abstract

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.

Item Type: Conference or Workshop Item
Erschienen: 2020
Creators: Terhorst, Philipp and Huber, Marco and Damer, Naser and Rot, Peter and Kirchbuchner, Florian and Struc, Vitomir and Kuijper, Arjan
Title: Privacy Evaluation Protocols for the Evaluation of Soft-Biometric Privacy-Enhancing Technologies
Language: English
Abstract:

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.

ISBN: 978-3-88579-700-5
Uncontrolled Keywords: Biometrics, Face recognition, Privacy enhancing technologies, Evaluation schemes, Machine learning
Divisions: 20 Department of Computer Science
20 Department of Computer Science > Interactive Graphics Systems
20 Department of Computer Science > Mathematical and Applied Visual Computing
Event Title: 19th International Conference of the Biometrics Special Interest Group (BIOSIG 2020)
Event Location: virtual Conference
Event Dates: 16.-18.09.
Date Deposited: 29 Sep 2020 07:49
Official URL: https://dl.gi.de/handle/20.500.12116/34330
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