Cancelable biometrics realization with multispace random projections

Andrew Beng Jin Teoh, Chong Tze Yuang

Research output: Contribution to journalArticlepeer-review

106 Citations (Scopus)

Abstract

Biometric characteristics cannot be changed; therefore, the loss of privacy is permanent if they are ever compromised. This paper presents a two-factor cancelable formulation, where the biometric data are distorted in a revocable but nonreversible manner by first transforming the raw biometric data into a fixed-length feature vector and then projecting the feature vector onto a sequence of random subspaces that were derived from a user-specific pseudorandom number (PRN). This process is revocable and makes replacing biometrics as easy as replacing PRNs. The formulation has been verified under a number of scenarios (normal, stolen PRN, and compromised biometrics scenarios) using 2400 Facial Recognition Technology face images. The diversity property is also examined.

Original languageEnglish
Pages (from-to)1096-1106
Number of pages11
JournalIEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Volume37
Issue number5
DOIs
Publication statusPublished - 2007 Oct

Bibliographical note

Funding Information:
Manuscript received April 29, 2006. This work was supported by the Korea Science and Engineering Foundation through the Biometrics Engineering Research Center, Yonsei University. This paper was recommended by Guest Editors V. Govindaraju and N. Ratha.

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Software
  • Information Systems
  • Human-Computer Interaction
  • Computer Science Applications
  • Electrical and Electronic Engineering

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