Fingerprint Template Protection Using Fuzzy Vault

2007 ◽  
pp. 1141-1151 ◽  
Author(s):  
Daesung Moon ◽  
Sungju Lee ◽  
Seunghwan Jung ◽  
Yongwha Chung ◽  
Miae Park ◽  
...  
Keyword(s):  
Fuzzy Vault ◽  
Template Protection

scholarly journals Palmprint Based Multidimensional Fuzzy Vault Scheme

2014 ◽  
Vol 2014 ◽  
pp. 1-8 ◽  
Author(s):  
Hailun Liu ◽  
Dongmei Sun ◽  
Ke Xiong ◽  
Zhengding Qiu
Keyword(s):  
Error Correcting Code ◽  
Experimental Results ◽  
Fuzzy Vault ◽  
Biometric Template ◽  
Template Protection ◽  
Biometric Template Protection

Fuzzy vault scheme (FVS) is one of the most popular biometric cryptosystems for biometric template protection. However, error correcting code (ECC) proposed in FVS is not appropriate to deal with real-valued biometric intraclass variances. In this paper, we propose a multidimensional fuzzy vault scheme (MDFVS) in which a general subspace error-tolerant mechanism is designed and embedded into FVS to handle intraclass variances. Palmprint is one of the most important biometrics; to protect palmprint templates; a palmprint based MDFVS implementation is also presented. Experimental results show that the proposed scheme not only can deal with intraclass variances effectively but also could maintain the accuracy and meanwhile enhance security.

Template protection approaches: Fuzzy Vault scheme

2019 ◽  
Author(s):  
Wendy Ponce-Hernandez ◽  
Ramon Blanco-Gonzalo ◽  
Raul Sanchez-Reillo ◽  
Judith Liu-Jimenez
Keyword(s):  
Fuzzy Vault ◽  
Template Protection

Cancellable fuzzy vault with periodic transformation for biometric template protection

2016 ◽  
Vol 5 (3) ◽  
pp. 229-235 ◽  
Author(s):  
Tran Khanh Dang ◽  
Quynh Chi Truong ◽  
Thu Thi Bao Le ◽  
Hai Truong
Keyword(s):  
Fuzzy Vault ◽  
Biometric Template ◽  
Template Protection ◽  
Periodic Transformation ◽  
Biometric Template Protection

Secure Chaff-less Fuzzy Vault for Face Identification Systems

2021 ◽  
Vol 17 (3) ◽  
pp. 1-22
Author(s):  
Xingbo Dong ◽  
Soohyong Kim ◽  
Zhe Jin ◽  
Jung Yeon Hwang ◽  
Sangrae Cho ◽  
...  
Keyword(s):  
Large Scale ◽  
Facial Features ◽  
Fuzzy Vault ◽  
Biometric Verification ◽  
Biometric Template ◽  
Template Protection ◽  
One To One ◽  
Face Datasets ◽  
Biometric Template Protection ◽  
Unconstrained Face

Biometric cryptosystems such as fuzzy vaults represent one of the most popular approaches for secret and biometric template protection. However, they are solely designed for biometric verification, where the user is required to input both identity credentials and biometrics. Several practical questions related to the implementation of biometric cryptosystems remain open, especially in regard to biometric template protection. In this article, we propose a face cryptosystem for identification (FCI) in which only biometric input is needed. Our FCI is composed of a one-to-N search subsystem for template protection and a one-to-one match chaff-less fuzzy vault (CFV) subsystem for secret protection. The first subsystem stores N facial features, which are protected by index-of-maximum (IoM) hashing, enhanced by a fusion module for search accuracy. When a face image of the user is presented, the subsystem returns the top k matching scores and activates the corresponding vaults in the CFV subsystem. Then, one-to-one matching is applied to the k vaults based on the probe face, and the identifier or secret associated with the user is retrieved from the correct matched vault. We demonstrate that coupling between the IoM hashing and the CFV resolves several practical issues related to fuzzy vault schemes. The FCI system is evaluated on three large-scale public unconstrained face datasets (LFW, VGG2, and IJB-C) in terms of its accuracy, computation cost, template protection criteria, and security.

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