Enhance Fuzzy Vault Security Using Nonrandom Chaff Point Generator

2014 ◽  
pp. 204-219 ◽  
Author(s):  
Minh Tan Nguyen ◽  
Quang Hai Truong ◽  
Tran Khanh Dang
Keyword(s):  
Fuzzy Vault

Cancelable fingerprint fuzzy vault scheme

2008 ◽  
Vol 28 (7) ◽  
pp. 1816-1818 ◽  
Author(s):  
Quan FENG
Keyword(s):  
Fuzzy Vault

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.

Chaff point generation mechanism for improving fuzzy vault security

2016 ◽  
Vol 5 (2) ◽  
pp. 147-153 ◽  
Author(s):  
Tran Khanh Dang ◽  
Minh Tan Nguyen ◽  
Quang Hai Truong
Keyword(s):  
Generation Mechanism ◽  
Fuzzy Vault

scholarly journals Secure Online Examination with Biometric Authentication and Blockchain-Based Framework

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Xiaoling Zhu ◽  
Chenglong Cao
Keyword(s):  
Access Control ◽  
Biometric Authentication ◽  
Fine Grained ◽  
Fuzzy Vault ◽  
Malicious Behavior ◽  
Online Examination ◽  
E Learning ◽  
Important Means ◽  
Biometric Templates ◽  
Biometric Features

E-learning has been carried out all over the world and then online examinations have become an important means to check learning effect during the outbreak of COVID-19. Participant authenticity, data integrity, and access control are the assurance to online examination. The existing online examination schemes cannot provide the protection of biometric features and fine-grained access control. Particularly, they did not discuss how to resolve some disputes among students, teachers, and a platform in a fair and reasonable way. We propose a novel biometric authentication and blockchain-based online examination scheme. The examination data are encrypted to store in a distributed system, which can be obtained only if the user satisfies decryption policy. And the pieces of evidence are recorded in a blockchain network which is jointly established by some credible institutions. Unlike other examination authentication systems, face templates in our scheme are protected using a fuzzy vault and a cryptographic method. Furthermore, educational administrative department can determine who the real initiator of malicious behavior is when a dispute arises using a dispute determination protocol. Analysis shows that no central authority is required in our scheme; the collusion of multiple users cannot obtain more data; even if the authorities compromise, biometric features of each user will not be leaked. Therefore, in terms of privacy-preserving biometric templates, fine-grained access, and dispute resolution, it is superior to the existing schemes.

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
Sign in / Sign up

Export Citation Format

Share Document