A tokenless cancellable scheme for multimodal biometric systems

Ming Jie Lee, Andrew Beng Jin Teoh, Andreas Uhl, Shiuan Ni Liang, Zhe Jin

Research output: Contribution to journalArticleResearchpeer-review

16 Citations (Scopus)

Abstract

Biometric template protection (BTP) is an open problem for biometric identity management systems. Cancellable biometrics is commonly designed to protect biometric templates with two input factors i.e., biometrics and a token used in template replacement. However, the token is often required to be kept secretly; otherwise, the protected template could be vulnerable to several security attacks and breaches of privacy. In this paper, we propose a tokenless cancellable biometrics scheme called Multimodal Extended Feature Vector (M∙EFV) Hashing that employs an improved XOR encryption/decryption notion to operate on the transformation key. We stress on multimodal biometrics where the real-valued face and fingerprint vectors are fused and embedded into a binarized cancellable template. Specifically, M∙EFV hashing consists of three stages of transformation: 1) normalization and biometric fusion; 2) randomization and binarization; and 3) cancellable template generation. To evaluate the proposed scheme, several benchmarking datasets, i.e., FVC2002, FVC2004 for fingerprint and LFW for face are used in experiments. The verification performance is validated by employing the FVC matching protocol. Various attacks are simulated and analysed in the worst-case scenario. Lastly, unlinkability and revocability properties are examined experimentally.

Original languageEnglish
Article number102350
Number of pages21
JournalComputers & Security
Volume108
DOIs
Publication statusPublished - Sept 2021

Keywords

  • Feature-level Fusion
  • Multimodal Biometrics
  • Privacy and security
  • Tokenless Cancellable Biometrics
  • XOR encryption/decryption

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