Secure Chaff-less Fuzzy Vault for Face Identification Systems

Xingbo Dong, Soohyong Kim, Zhe Jin, Jung Yeon Hwang, Sangrae Cho, Andrew Beng Jin Teoh

Research output: Contribution to journalArticlepeer-review

4 Citations (Scopus)


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.

Original languageEnglish
Article number79
JournalACM Transactions on Multimedia Computing, Communications and Applications
Issue number3
Publication statusPublished - 2021 Aug

Bibliographical note

Funding Information:
This work was supported by the Institute for Information & Communications Technology Promotion (IITP) via grants funded by the Korean government (MSIT) (No. 2016-0-00097, Development of Biometrics-based Key Infrastructure Technology for On-line Identification, and No. 2018-0-00189, Security Technology for Portal Device to Connect Human-Infrastructure-Service in Highly Trusted Intelligent Information Service). Authors’ addresses: X. Dong and Z. Jin, School of Information Technology, Monash University Malaysia, Malaysia; emails: {Xingbo.Dong, Jin.Zhe}; S. Kim and S. Cho, Electronics and Telecommunications Research Institute (ETRI), Daejeon, Republic of Korea; emails: {lifewsky, sangrae}; J. Hwang, Department of Mathematics, Sungshin Women’s University, Seoul, Republic of Korea; email:; A. B. J. Teoh, School of Electrical and Electronic Engineering, Yonsei University, Seoul, Republic of Korea; email: Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from © 2021 Association for Computing Machinery. 1551-6857/2021/07-ART79 $15.00

Publisher Copyright:
© 2021 Association for Computing Machinery.

All Science Journal Classification (ASJC) codes

  • Hardware and Architecture
  • Computer Networks and Communications


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