A real helper data scheme

X. Shao; Raymond N.J. Veldhuis

doi:10.1109/ACPR.2013.29

A real helper data scheme

X. Shao
, Raymond N.J. Veldhuis

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

1 Citation (Scopus)

195 Downloads (Pure)

Abstract

The helper data scheme utilizes a secret key to protect biometric templates. The current helper data scheme requires binary feature representations that introduce quantization error and thus reduce the capacity of biometric channels. For spectral-minutiae based fingerprint recognition systems, Shannon theory proves that the current helper data scheme cannot have more than 6 bits. A 6-bit secret key is too short to secure the storage of biometric templates. Therefore, we propose a new helper data scheme without quantization. A basic realization is to convert the real-valued feature vector into a phase vector. By applying the spectral minutiae method in the FVC2000-DB2 fingerprint database, our new helper data scheme together with repetition codes and BCH codes allows at least 76 secret bits.

Original language	Undefined
Title of host publication	Proceedings of the 2nd IAPR Asian Conference on Pattern Recognition (ACPR), 2013
Place of Publication	USA
Publisher	IEEE
Pages	84-89
Number of pages	6
ISBN (Print)	978-1-4799-2190-4
DOIs	https://doi.org/10.1109/ACPR.2013.29
Publication status	Published - 5 Nov 2013
Event	2nd IAPR Asian Conference on Pattern Recognition, ACPR 2013 - Okinawa, Japan Duration: 5 Nov 2013 → 8 Nov 2013 Conference number: 2 http://www.am.sanken.osaka-u.ac.jp/ACPR2013/

Publication series

Name
Publisher	IEEE Computer Society

Conference

Conference	2nd IAPR Asian Conference on Pattern Recognition, ACPR 2013
Abbreviated title	ACPR 2013
Country/Territory	Japan
City	Okinawa
Period	5/11/13 → 8/11/13
Internet address	http://www.am.sanken.osaka-u.ac.jp/ACPR2013/

Keywords

EWI-25560
helper data scheme
METIS-309811
Biometric recognition
IR-93501
Biometric Template Protection

Access to Document

10.1109/ACPR.2013.29

Shao13_A_real_helper_data_scheme

Cite this

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title = "A real helper data scheme",

abstract = "The helper data scheme utilizes a secret key to protect biometric templates. The current helper data scheme requires binary feature representations that introduce quantization error and thus reduce the capacity of biometric channels. For spectral-minutiae based fingerprint recognition systems, Shannon theory proves that the current helper data scheme cannot have more than 6 bits. A 6-bit secret key is too short to secure the storage of biometric templates. Therefore, we propose a new helper data scheme without quantization. A basic realization is to convert the real-valued feature vector into a phase vector. By applying the spectral minutiae method in the FVC2000-DB2 fingerprint database, our new helper data scheme together with repetition codes and BCH codes allows at least 76 secret bits.",

keywords = "EWI-25560, helper data scheme, METIS-309811, Biometric recognition, IR-93501, Biometric Template Protection",

author = "X. Shao and Veldhuis, \{Raymond N.J.\}",

note = "eemcs-eprint-25560 ; 2nd IAPR Asian Conference on Pattern Recognition, ACPR 2013 ; Conference date: 05-11-2013 Through 08-11-2013",

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AB - The helper data scheme utilizes a secret key to protect biometric templates. The current helper data scheme requires binary feature representations that introduce quantization error and thus reduce the capacity of biometric channels. For spectral-minutiae based fingerprint recognition systems, Shannon theory proves that the current helper data scheme cannot have more than 6 bits. A 6-bit secret key is too short to secure the storage of biometric templates. Therefore, we propose a new helper data scheme without quantization. A basic realization is to convert the real-valued feature vector into a phase vector. By applying the spectral minutiae method in the FVC2000-DB2 fingerprint database, our new helper data scheme together with repetition codes and BCH codes allows at least 76 secret bits.

KW - EWI-25560

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KW - METIS-309811

KW - Biometric recognition

KW - IR-93501

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