International Journal of Computational Intelligence Systems

Volume 8, Issue 6, December 2015, Pages 1116 - 1127

Secure and Efficient Biometric-Data Binarization using Multi-Objective Optimization

Authors
Eslam Hamouda, Xiaohui Yuan, Osama Ouda, Taher Hamza
Corresponding Author
Eslam Hamouda
Received 8 December 2014, Accepted 5 October 2015, Available Online 1 December 2015.
DOI
10.1080/18756891.2015.1113746How to use a DOI?
Keywords
Biometrics, Binarization, Quantization, Encoding, Multi-objective Optimization
Abstract

Biometric system databases are vulnerable to many types of attacks. To address this issue, several biometric template protection systems have been proposed to protect biometric data against unauthorized use. Many of biometric protection systems require the biometric templates to be represented in a binary form. Therefore, extracting binary templates from real-valued biometric data is a key step in such biometric data protection systems. In addition, binary representation of biometric data can speed-up the matching process and reduce the storage capacity required to store the enrolled templates. The main challenge of existing biometric data binarization approaches is to retain the discrimination power of the original real-valued templates after binarization. In this paper, we propose a secure and efficient biometric data binarization scheme that employs multi-objective optimization using Nondominated Sorting Genetic Algorithm (NSGA-II). The goal of the proposed method is to find optimal quantization and encoding parameters that are employed in the binarization process. Results obtained from the experiments conducted on the ORL face and MCYT fingerprint databases show a promising recognition accuracy without sacrificing the security of the system.

Copyright
© 2017, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Journal
International Journal of Computational Intelligence Systems
Volume-Issue
8 - 6
Pages
1116 - 1127
Publication Date
2015/12/01
ISSN (Online)
1875-6883
ISSN (Print)
1875-6891
DOI
10.1080/18756891.2015.1113746How to use a DOI?
Copyright
© 2017, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - JOUR
AU  - Eslam Hamouda
AU  - Xiaohui Yuan
AU  - Osama Ouda
AU  - Taher Hamza
PY  - 2015
DA  - 2015/12/01
TI  - Secure and Efficient Biometric-Data Binarization using Multi-Objective Optimization
JO  - International Journal of Computational Intelligence Systems
SP  - 1116
EP  - 1127
VL  - 8
IS  - 6
SN  - 1875-6883
UR  - https://doi.org/10.1080/18756891.2015.1113746
DO  - 10.1080/18756891.2015.1113746
ID  - Hamouda2015
ER  -