Sparse Combined Index-of-Max Hashing for Fingerprint Template Protection

Jihyeon Kim; Andrew Beng Jin Teoh

doi:10.1109/CISP-BMEI48845.2019.8965716

Sparse Combined Index-of-Max Hashing for Fingerprint Template Protection

Jihyeon Kim, Andrew Beng Jin Teoh

Department of Electrical and Electronic Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

3 Citations (Scopus)

Abstract

In this paper, a cancellable biometric scheme called Sparse Combined Index-of-Maximum (SC-IoM) hashing is proposed. SC-IoM hashing is designed on top of IoM hashing proposed recently. Unlike IoM hashing, SC-IoM hashing acquires indices of the largest and second largest user-specific random projected biometric features, thus produce two set integer-valued vectors. Two hash vectors are further nonlinearly transformed into sparse binary vectors via a probabilistic many-to-one function, which is manifested in a Lookup Table form. Finally, two sparse binary vectors are mixed intersectly and yield a compact single sparse binary vector. The security and privacy of the SC-IoM hashing are enhanced over IoM hashing yet provides better accuracy performance. Both revocability and unlinkability criteria remain satisfied. The scheme is evaluated with fingerprint vectors under FVC2002 and FVC2004 fingerprint benchmark datasets.

Original language	English
Title of host publication	Proceedings - 2019 12th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI 2019
Editors	Qingli Li, Lipo Wang
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781728148526
DOIs	https://doi.org/10.1109/CISP-BMEI48845.2019.8965716
Publication status	Published - 2019 Oct
Event	12th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI 2019 - Huaqiao, China Duration: 2019 Oct 19 → 2019 Oct 21

Publication series

Name	Proceedings - 2019 12th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI 2019

Conference

Conference	12th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI 2019
Country/Territory	China
City	Huaqiao
Period	19/10/19 → 19/10/21

Bibliographical note

Funding Information:
ACKNOWLEDGEMENT This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIP) (NO. NRF-2019R1A2C1003306)

Funding Information:
This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIP) (NO. NRF-2019R1A2C1003306)

Publisher Copyright:
© 2019 IEEE.

All Science Journal Classification (ASJC) codes

Information Systems
Signal Processing
Biomedical Engineering
Computer Vision and Pattern Recognition
Information Systems and Management

Access to Document

10.1109/CISP-BMEI48845.2019.8965716

Cite this

Kim, J., & Jin Teoh, A. B. (2019). Sparse Combined Index-of-Max Hashing for Fingerprint Template Protection. In Q. Li, & L. Wang (Eds.), Proceedings - 2019 12th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI 2019 [8965716] (Proceedings - 2019 12th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI 2019). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CISP-BMEI48845.2019.8965716

Kim, Jihyeon ; Jin Teoh, Andrew Beng. / Sparse Combined Index-of-Max Hashing for Fingerprint Template Protection. Proceedings - 2019 12th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI 2019. editor / Qingli Li ; Lipo Wang. Institute of Electrical and Electronics Engineers Inc., 2019. (Proceedings - 2019 12th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI 2019).

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title = "Sparse Combined Index-of-Max Hashing for Fingerprint Template Protection",

abstract = "In this paper, a cancellable biometric scheme called Sparse Combined Index-of-Maximum (SC-IoM) hashing is proposed. SC-IoM hashing is designed on top of IoM hashing proposed recently. Unlike IoM hashing, SC-IoM hashing acquires indices of the largest and second largest user-specific random projected biometric features, thus produce two set integer-valued vectors. Two hash vectors are further nonlinearly transformed into sparse binary vectors via a probabilistic many-to-one function, which is manifested in a Lookup Table form. Finally, two sparse binary vectors are mixed intersectly and yield a compact single sparse binary vector. The security and privacy of the SC-IoM hashing are enhanced over IoM hashing yet provides better accuracy performance. Both revocability and unlinkability criteria remain satisfied. The scheme is evaluated with fingerprint vectors under FVC2002 and FVC2004 fingerprint benchmark datasets.",

author = "Jihyeon Kim and {Jin Teoh}, {Andrew Beng}",

note = "Funding Information: ACKNOWLEDGEMENT This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIP) (NO. NRF-2019R1A2C1003306) Funding Information: This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIP) (NO. NRF-2019R1A2C1003306) Publisher Copyright: {\textcopyright} 2019 IEEE.; 12th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI 2019 ; Conference date: 19-10-2019 Through 21-10-2019",

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Kim, J & Jin Teoh, AB 2019, Sparse Combined Index-of-Max Hashing for Fingerprint Template Protection. in Q Li & L Wang (eds), Proceedings - 2019 12th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI 2019., 8965716, Proceedings - 2019 12th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI 2019, Institute of Electrical and Electronics Engineers Inc., 12th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI 2019, Huaqiao, China, 19/10/19. https://doi.org/10.1109/CISP-BMEI48845.2019.8965716

Sparse Combined Index-of-Max Hashing for Fingerprint Template Protection. / Kim, Jihyeon; Jin Teoh, Andrew Beng.

Proceedings - 2019 12th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI 2019. ed. / Qingli Li; Lipo Wang. Institute of Electrical and Electronics Engineers Inc., 2019. 8965716 (Proceedings - 2019 12th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI 2019).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

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AU - Kim, Jihyeon

AU - Jin Teoh, Andrew Beng

N1 - Funding Information: ACKNOWLEDGEMENT This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIP) (NO. NRF-2019R1A2C1003306) Funding Information: This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIP) (NO. NRF-2019R1A2C1003306) Publisher Copyright: © 2019 IEEE.

PY - 2019/10

Y1 - 2019/10

N2 - In this paper, a cancellable biometric scheme called Sparse Combined Index-of-Maximum (SC-IoM) hashing is proposed. SC-IoM hashing is designed on top of IoM hashing proposed recently. Unlike IoM hashing, SC-IoM hashing acquires indices of the largest and second largest user-specific random projected biometric features, thus produce two set integer-valued vectors. Two hash vectors are further nonlinearly transformed into sparse binary vectors via a probabilistic many-to-one function, which is manifested in a Lookup Table form. Finally, two sparse binary vectors are mixed intersectly and yield a compact single sparse binary vector. The security and privacy of the SC-IoM hashing are enhanced over IoM hashing yet provides better accuracy performance. Both revocability and unlinkability criteria remain satisfied. The scheme is evaluated with fingerprint vectors under FVC2002 and FVC2004 fingerprint benchmark datasets.

AB - In this paper, a cancellable biometric scheme called Sparse Combined Index-of-Maximum (SC-IoM) hashing is proposed. SC-IoM hashing is designed on top of IoM hashing proposed recently. Unlike IoM hashing, SC-IoM hashing acquires indices of the largest and second largest user-specific random projected biometric features, thus produce two set integer-valued vectors. Two hash vectors are further nonlinearly transformed into sparse binary vectors via a probabilistic many-to-one function, which is manifested in a Lookup Table form. Finally, two sparse binary vectors are mixed intersectly and yield a compact single sparse binary vector. The security and privacy of the SC-IoM hashing are enhanced over IoM hashing yet provides better accuracy performance. Both revocability and unlinkability criteria remain satisfied. The scheme is evaluated with fingerprint vectors under FVC2002 and FVC2004 fingerprint benchmark datasets.

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M3 - Conference contribution

AN - SCOPUS:85079184945

T3 - Proceedings - 2019 12th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI 2019

BT - Proceedings - 2019 12th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI 2019

A2 - Li, Qingli

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PB - Institute of Electrical and Electronics Engineers Inc.

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Kim J, Jin Teoh AB. Sparse Combined Index-of-Max Hashing for Fingerprint Template Protection. In Li Q, Wang L, editors, Proceedings - 2019 12th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI 2019. Institute of Electrical and Electronics Engineers Inc. 2019. 8965716. (Proceedings - 2019 12th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI 2019). doi: 10.1109/CISP-BMEI48845.2019.8965716

Sparse Combined Index-of-Max Hashing for Fingerprint Template Protection

Abstract

Publication series

Conference

Bibliographical note

All Science Journal Classification (ASJC) codes

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