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A False Sense of Privacy: Towards a Reliable Evaluation Methodology for the Anonymization of Biometric Data

Hanisch, Simon 1; Todt, Julian 2; Patino, Jose; Evans, Nicholas; Strufe, Thorsten ORCID iD icon 2
1 Technische Universität Dresden (TU Dresden)
2 Kompetenzzentrum für angewandte Sicherheitstechnologie (KASTEL), Karlsruher Institut für Technologie (KIT)

Abstract (englisch):

Biometric data contains distinctive human traits such as facial features or gait patterns. The use of biometric data permits an individuation so exact that the data is utilized effectively in identification and authentication systems. But for this same reason, privacy protections become indispensably necessary. Privacy protection is extensively afforded by the technique of anonymization. Anonymization techniques protect sensitive personal data from biometrics by obfuscating or removing information that allows linking records to the generating individuals, to achieve high levels of anonymity. However, our understanding and possibility to develop effective anonymization relies, in equal parts, on the effectiveness of the methods employed to evaluate anonymization performance. In this paper, we assess the state-of-the-art methods used to evaluate the performance of anonymization techniques for facial images and for gait patterns. We demonstrate that the state-of-the-art evaluation methods have serious and frequent shortcomings. In particular, we find that the underlying assumptions of the state-of-the-art are quite unwarranted. State-of-the-art methods generally assume a difficult recognition scenario and thus a weak adversary. ... mehr


Verlagsausgabe §
DOI: 10.5445/IR/1000163313
Veröffentlicht am 24.10.2023
Originalveröffentlichung
DOI: 10.56553/popets-2024-0008
Dimensions
Zitationen: 1
Cover der Publikation
Zugehörige Institution(en) am KIT Kompetenzzentrum für angewandte Sicherheitstechnologie (KASTEL)
Publikationstyp Zeitschriftenaufsatz
Publikationsjahr 2024
Sprache Englisch
Identifikator ISSN: 2299-0984
KITopen-ID: 1000163313
HGF-Programm 46.23.01 (POF IV, LK 01) Methods for Engineering Secure Systems
Erschienen in Proceedings on Privacy Enhancing Technologies
Verlag De Gruyter
Band 2024
Heft 1
Seiten 116–132
Vorab online veröffentlicht am 23.10.2023
Schlagwörter privacy, biometric, methodology, anonymization, evaluation
Nachgewiesen in Dimensions
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