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.

scholarly journals A Hybrid Approach to Protect Palmprint Templates

2014 ◽  
Vol 2014 ◽  
pp. 1-9 ◽  
Author(s):  
Hailun Liu ◽  
Dongmei Sun ◽  
Ke Xiong ◽  
Zhengding Qiu
Keyword(s):  
Large Scale ◽  
Hybrid Approach ◽  
Random Projection ◽  
Personal Privacy ◽  
Fuzzy Vault ◽  
Biometric Template ◽  
Biometric Systems ◽  
Template Protection ◽  
Theoretical Analyses ◽  
Biometric Template Protection

Biometric template protection is indispensable to protect personal privacy in large-scale deployment of biometric systems. Accuracy, changeability, and security are three critical requirements for template protection algorithms. However, existing template protection algorithms cannot satisfy all these requirements well. In this paper, we propose a hybrid approach that combines random projection and fuzzy vault to improve the performances at these three points. Heterogeneous space is designed for combining random projection and fuzzy vault properly in the hybrid scheme. New chaff point generation method is also proposed to enhance the security of the heterogeneous vault. Theoretical analyses of proposed hybrid approach in terms of accuracy, changeability, and security are given in this paper. Palmprint database based experimental results well support the theoretical analyses and demonstrate the effectiveness of proposed hybrid approach.

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.

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

Significance of the Transition to Biometric Template Protection: Explore the Future

2020 ◽  
pp. 2150025
Author(s):  
Ayesha S. Shaikh ◽  
Vibha D. Patel
Keyword(s):  
Privacy Preserving ◽  
Handheld Devices ◽  
Cancelable Biometrics ◽  
Discrete Cosine Transformation ◽  
Biometric Template ◽  
Template Protection ◽  
Novel Method ◽  
Identity Based ◽  
The Government ◽  
Biometric Template Protection

The IT security paradigm evolves from secret-based to biometric identity-based. Biometric identification has gradually become more popular in recent years for handheld devices. Privacy-preserving is a key concern when biometrics is used in authentication systems in the present world today. Nowadays, the declaration of biometric traits has been imposed not only by the government but also by many private entities. There are no proper mechanisms and assurance that biometric traits will be kept safe by such entities. The encryption of biometric traits to avoid privacy attacks is a giant problem. Hence, state-of-the-art safety and security technological solutions must be devised to prevent the loss and misuse of such biometric traits. In this paper, we have identified different cancelable biometrics methods with the possible attacks on the biometric traits and directions on possible countermeasures in order to design a secure and privacy-preserving biometric authentication system. We also proposed a highly secure method for cancelable biometrics using a non-invertible function based on Discrete Cosine Transformation and Index of max hashing. We tested and evaluated the proposed novel method on a standard dataset and achieved good results.

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