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Proceedings Paper

Privacy protection schemes for fingerprint recognition systems
Author(s): Emanuela Marasco; Bojan Cukic
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Paper Abstract

The deployment of fingerprint recognition systems has always raised concerns related to personal privacy. A fingerprint is permanently associated with an individual and, generally, it cannot be reset if compromised in one application. Given that fingerprints are not a secret, potential misuses besides personal recognition represent privacy threats and may lead to public distrust. Privacy mechanisms control access to personal information and limit the likelihood of intrusions. In this paper, image- and feature-level schemes for privacy protection in fingerprint recognition systems are reviewed. Storing only key features of a biometric signature can reduce the likelihood of biometric data being used for unintended purposes. In biometric cryptosystems and biometric-based key release, the biometric component verifies the identity of the user, while the cryptographic key protects the communication channel. Transformation-based approaches only a transformed version of the original biometric signature is stored. Different applications can use different transforms. Matching is performed in the transformed domain which enable the preservation of low error rates. Since such templates do not reveal information about individuals, they are referred to as cancelable templates. A compromised template can be re-issued using a different transform. At image-level, de-identification schemes can remove identifiers disclosed for objectives unrelated to the original purpose, while permitting other authorized uses of personal information. Fingerprint images can be de-identified by, for example, mixing fingerprints or removing gender signature. In both cases, degradation of matching performance is minimized.

Paper Details

Date Published: 15 May 2015
PDF: 14 pages
Proc. SPIE 9457, Biometric and Surveillance Technology for Human and Activity Identification XII, 94570D (15 May 2015); doi: 10.1117/12.2178978
Show Author Affiliations
Emanuela Marasco, The Univ. of North Carolina at Charlotte (United States)
Bojan Cukic, The Univ. of North Carolina at Charlotte (United States)


Published in SPIE Proceedings Vol. 9457:
Biometric and Surveillance Technology for Human and Activity Identification XII
Ioannis A. Kakadiaris; Ajay Kumar; Walter J. Scheirer, Editor(s)

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