NDBIris with Better Unlinkability (original) (raw)

2020

Abstract

Iris recognition is one of the mainstream biometric recognition methods. Protecting iris data to prevent personal privacy leakage is significant to the popularity of iris recognition. Negative database is a new type of privacy protection technique. We proposed a promising method (called NDBIris) of iris template protection based on negative databases in previous work. However, its unlinkability is vulnerable under typical parameter settings (e.g. p1=0.8$,p_{2}$=0.14) and it does not protect the privacy of real-time iris data from users for recognition. This paper proposes an improved version called NDBIris-II to achieve better unlinkability and protect the real-time iris data. Specifically, a noninvertible transform using local sorting is performed before converting iris data into negative databases. Moreover, a method for estimating the similarity between iris data from negative databases is proposed to support effective iris recognition. Finally, an iris template in the form of ne...

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