Fractional biometrics: Safeguarding privacy in biometric applications

Duncan Bayly, Maurice Castro, Arathi Arakala, Jason Jeffers, Kathy J. Horadam

Research output: Contribution to journalArticleResearchpeer-review

5 Citations (Scopus)


This paper presents a biometric system solution that "masks" a fraction of a person's biometric image before submission, to reduce the possibility of forgery and collusion. A prototype system was constructed for the fingerprint biometric and tested in three security scenarios. It is shown that implementing the fractional biometric system does not significantly affect accuracy. We provide theoretical security analysis on the guessing entropy of a Fractional Template and the security against collusion. We demonstrate that by masking above 50% of the biometric features, we achieve a sufficient mix of security, robustness and accuracy to warrant further study. When 75% of the features are masked, we found that the theoretical guessing entropy is 42 bits, and we found that, on average, 5 authenticators had to collude before the system would be compromised.

Original languageEnglish
Pages (from-to)69-82
Number of pages14
JournalInternational Journal of Information Security
Issue number1
Publication statusPublished - Jan 2010
Externally publishedYes


  • Biometrics
  • Fingerprint
  • Privacy
  • Relationship pseudonymity

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