Design of cancelable MCC-based fingerprint templates using dyno-key model

Abstract

Minutia Cylinder Code (MCC) is an effective, high-quality representation of local minutia structures. MCC templates demonstrate fast and excellent fingerprint matching performance, but if compromised, they can be reverse-engineered to retrieve minutia information. In this paper, we propose alignment-free cancelable MCC-based templates by exploiting the MCC feature extraction and representation. The core component of our design is a dynamic random key model, called Dyno-key model. The Dyno-key model dynamically extracts elements from MCC's binary feature vectors based on randomly generated keys. Those extracted elements are discarded after the block-based logic operations so as to increase security. Leveling with the performance of the unprotected, reproduced MCC templates, the proposed method exhibits competitive performance in comparison with state-of-the-art cancelable fingerprint templates, as evaluated over seven public databases, FVC2002 DB1-DB3, FVC2004 DB1 and DB2, and FVC2006 DB2 and DB3. The proposed cancelable MCC-based templates satisfy all the requirements of biometric template protection.

Keywords

Alignment-free, Biometric template protection, Cancelable biometrics, Cancelable fingerprint templates, Minutia cylinder code

Document Type

Journal Article

Date of Publication

2021

Volume

119

Publication Title

Pattern Recognition

Publisher

Elsevier

School

School of Science / ECU Security Research Institute

RAS ID

36146

Comments

Bedari, A., Wang, S., & Yang, W. (2021). Design of cancelable MCC-based fingerprint templates using dyno-key model. Pattern Recognition, 119, article 108074. https://doi.org/10.1016/j.patcog.2021.108074

Copyright

subscription content

Link to Full Text

Share

 
COinS
 

Link to publisher version (DOI)

10.1016/j.patcog.2021.108074