Privacy-protected biometric templates: acoustic ear identification

Pim T. Tuyls; Evgeny Verbitskiy; Tanya Ignatenko; Daniel Schobben; Ton H. Akkermans

doi:10.1117/12.541882

25 August 2004 Privacy-protected biometric templates: acoustic ear identification

Pim T. Tuyls, Evgeny Verbitskiy, Tanya Ignatenko, Daniel Schobben, Ton H. Akkermans

Proceedings Volume 5404, Biometric Technology for Human Identification; (2004) https://doi.org/10.1117/12.541882
Event: Defense and Security, 2004, Orlando, Florida, United States

Abstract

Unique Biometric Identifiers offer a very convenient way for human identification and authentication. In contrast to passwords they have hence the advantage that they can not be forgotten or lost. In order to set-up a biometric identification/authentication system, reference data have to be stored in a central database. As biometric identifiers are unique for a human being, the derived templates comprise unique, sensitive and therefore private information about a person. This is why many people are reluctant to accept a system based on biometric identification. Consequently, the stored templates have to be handled with care and protected against misuse [1, 2, 3, 4, 5, 6]. It is clear that techniques from cryptography can be used to achieve privacy. However, as biometric data are noisy, and cryptographic functions are by construction very sensitive to small changes in their input, and hence one can not apply those crypto techniques straightforwardly. In this paper we show the feasibility of the techniques developed in [5], [6] by applying them to experimental biometric data. As biometric identifier we have choosen the shape of the inner ear-canal, which is obtained by measuring the headphone-to-ear-canal Transfer Functions (HpTFs) which are known to be person dependent [7].

Citation Download Citation

Pim T. Tuyls, Evgeny Verbitskiy, Tanya Ignatenko, Daniel Schobben, and Ton H. Akkermans "Privacy-protected biometric templates: acoustic ear identification", Proc. SPIE 5404, Biometric Technology for Human Identification, (25 August 2004); https://doi.org/10.1117/12.541882

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