DocumentCode
2307702
Title
A two -step hybrid approach for voiceprint-biometric template protection
Author
Zhu, Hua-hong ; He, Qian-hua ; Li, Yan-xiong
Author_Institution
Sch. of Electron. & Inf. Eng., South China Univ. of Technol., Guangzhou, China
Volume
2
fYear
2012
fDate
15-17 July 2012
Firstpage
560
Lastpage
565
Abstract
Biometric template protection is a crucial issue to be addressed for widespread deployment of biometrics-based recognition systems in real life application. Although a number of biometric template protection methods have been reported, it is still a challenging task to devise a scheme to satisfy both security and performance. In this paper, a two-step hybrid approach is proposed to generate a cancelable voiceprint template utilizing the advantages of both Template Transformation and Biometric Cryptosystem. The original voiceprint is transformed with random matrix based on the similarity-preserving of random projection. Chaff points are added to the codebook and matching is also performed in the transformed domain. Random projection improves the cancelability while chaff points conceal the genuine codeword to enhance the security. Binary indexes help identify the genuine codeword accurately. The effectiveness of the proposed method is well supported by detailed analysis. The experimental results demonstrate that the recognition performance is well-kept as the original template does.
Keywords
biometrics (access control); cryptography; matrix algebra; security of data; speaker recognition; binary indexes; biometric cryptosystem; biometric template protection methods; biometric-based recognition systems; cancelable voiceprint template transformation; chaff points; codebook; codeword identification; random matrix; random projection similarity-preserving; two-step hybrid approach; voiceprint-biometric template protection; Abstracts; Biomedical measurements; Cryptography; Speech recognition; Fuzzy vault; Random projection; Template protection; Voiceprint;
fLanguage
English
Publisher
ieee
Conference_Titel
Machine Learning and Cybernetics (ICMLC), 2012 International Conference on
Conference_Location
Xian
ISSN
2160-133X
Print_ISBN
978-1-4673-1484-8
Type
conf
DOI
10.1109/ICMLC.2012.6358984
Filename
6358984
Link To Document