Research Article
Wavelet Based Feature Level Fusion Approach for Multi-biometric Cryptosystem
@INPROCEEDINGS{10.1007/978-3-319-73712-6_28, author={Patel Heena and Paunwala Chirag and Vora Aarohi}, title={Wavelet Based Feature Level Fusion Approach for Multi-biometric Cryptosystem}, proceedings={Future Internet Technologies and Trends. First International Conference, ICFITT 2017, Surat, India, August 31 - September 2, 2017, Proceedings}, proceedings_a={ICFITT}, year={2018}, month={2}, keywords={Authentication Biometric encryption/decryption Biometric template protection Cryptography Wavelet}, doi={10.1007/978-3-319-73712-6_28} }- Patel Heena
Paunwala Chirag
Vora Aarohi
Year: 2018
Wavelet Based Feature Level Fusion Approach for Multi-biometric Cryptosystem
ICFITT
Springer
DOI: 10.1007/978-3-319-73712-6_28
Abstract
Biometric cryptosystems incorporates the benefits of both cryptography as well as biometrics i.e. higher security levels and elimination of memorizing passwords or carrying tokens. The threat of breaching the security of the confidential data motivates the development of the data hiding techniques in this paper. This paper contributes in enhancing the security of biometric systems by incorporating the concept of wavelet decomposition along with the fusion of biometric traits. The concept of wavelet decomposition of feature templates helps in reduction of template size as well as it increases the compatibility of the templates of different biometric traits. The biometric key is generated from a biometric construct using proposed cryptographic key extraction algorithm and then the key is applied on fused template to protect the template from various attacks. The implementation results obtained provides 100% GAR at 17% FAR i.e. authentication performance of the system is better as compared to other systems.
