Minutiae matching with privacy protection based on the combination of garbled circuit and homomorphic encryption.
Biometrics plays an important role in authentication applications since they are strongly linked to holders. With an increasing growth of e-commerce and e-government, one can expect that biometric-based authentication systems are possibly deployed over the open networks in the near future. However, due to its openness, the Internet poses a great challenge to the security and privacy of biometric authentication. Biometric data cannot be revoked, so it is of paramount importance that biometric data should be handled in a secure way. In this paper we present a scheme achieving privacy-preserving fingerprint authentication between two parties, in which fingerprint minutiae matching algorithm is completed in the encrypted domain. To improve the efficiency, we exploit homomorphic encryption as well as garbled circuits to design the protocol. Our goal is to provide protection for the security of template in storage and data privacy of two parties in transaction. The experimental results show that the proposed authentication protocol runs efficiently. Therefore, the protocol can run over open networks and help to alleviate the concerns on security and privacy of biometric applications over the open networks.
School of Communication and Electronic Engineering, Hunan City University, Yiyang, Hunan 41300, China.
Mengxing
M
Li
Engineering College, Gansu Agricultural University, Anning District, Lanzhou 730070, China.
Quan
0000-0002-6368-3975
Q
Feng
Engineering College, Gansu Agricultural University, Anning District, Lanzhou 730070, China.
Jian
J
Zhao
Engineering College, Gansu Agricultural University, Anning District, Lanzhou 730070, China.
Mei
M
Yang
College of Information Sciences and Technology, Gansu Agricultural University, Anning District, Lanzhou 730070, China.
Lijun
L
Kang
College of Information Sciences and Technology, Gansu Agricultural University, Anning District, Lanzhou 730070, China.
Lili
L
Wu
D000465:Algorithms; D056667:Biometric Identification; D006801:Humans; D008962:Models, Theoretical; D018907:Privacy