Abstract
In recent years, biometrics template protection has been extensively studied and lots of schemes have been proposed. However, most of them have not considered the forgery, large difference of intra-class and the security of unimodal biometrics leakage. And there is no multibiometrics template scheme based on the fusion of dual iris, thermal and visible face images. In this paper, a novel multibiometrics template protection scheme based on fuzzy commitment and chaotic system, and the security analysis approach for unimodal biometrics leakage are proposed. Firstly, the thermal face images are captured to overcome the forgery. Then, the fuzzy commitment is generated from the corporation of error correcting code (ECC) and the fusion binary features. Additionally, the dual iris feature vectors are encrypted via the chaotic system, and the score level fusion based on Aczel-Alsina triangular-norm (AA T-norm) is implemented to acquire the final verification performance. Finally, the entropy of both mutlibiometrics and unimodal information leakage is analyzed to show the security of the proposed approach. The experimental tests are conducted on a virtual multibiometrics database, which merges the challenging CASIA-Iris-Thousand and the NVIE face database. The verification performance decreases from EER of 3 x 10(-2) to 1.163 x 10(-1) %, but the multibiometrics template security is enhanced from 80.53 to 167.80 bits based on BCH ECC (1,023, 123, 170).