Paper Info
Title
A Biometric Cryptosystem Scheme Based On Random Projection And Neural Network
Abstract
Several biometric cryptosystem techniques have been proposed to protect biometric templates and preserve users' privacy. Although such techniques can thwart different attacks, it is difficult to achieve well non-linkability between biometric cryptosystems. In this paper, we propose a novel biometric cryptosystem scheme based on random projection (RP) and back propagation neural network (BPNN) to perform the task of biometric template protection. With the help of RP, an original biometric feature vector can be projected onto a fix-length feature vector of random subspace that is derived from a user-specific projection matrix. This process is revocable and produces unlinkable biometric templates. The proposed scheme further utilizes a BPNN model to bind a projected feature vector with a random key. Based on BPNN, a robust mapping between a projected feature vector and a random key is learned to generate an error-correction-based biometric cryptosystem. The security of the proposed scheme is analyzed and the experimental results on multiple biometric datasets show the feasibility and efficiency of the proposed scheme.
Year
DOI
Venue
2021
10.1007/s00500-021-05732-2
SOFT COMPUTING
Keywords
DocType
Volume
Biometric template protection, Biometric cryptosystem, Random projection, Back propagation neural network
Journal
25
Issue
ISSN
Citations 
11
1432-7643
1
PageRank 
References 
Authors
0.35
0
4
Name
Order
Citations
PageRank
Jialiang Peng1798.19
Bian Yang2397.71
Brij B. Gupta310.35
Ahmed A. Abd El-Latif410.69