Security of biometric templates stored in a system is important because a stolen template can compromise
system security as well as user privacy. Therefore, a number of secure biometrics schemes have been proposed
that facilitate matching of feature templates without the need for a stored biometric sample. However, most of
these schemes suffer from poor matching performance owing to the difficulty of designing biometric features that
remain robust over repeated biometric measurements. This paper describes a scheme to extract binary features
from fingerprints using minutia points and fingerprint ridges. The features are amenable to direct matching
based on binary Hamming distance, but are especially suitable for use in secure biometric cryptosystems that
use standard error correcting codes. Given all binary features, a method for retaining only the most discriminable
features is presented which improves the Genuine Accept Rate (GAR) from 82% to 90% at a False Accept Rate
(FAR) of 0.1% on a well-known public database. Additionally, incorporating singular points such as a core or
delta feature is shown to improve the matching tradeoff.
One of the critical steps in designing a secure biometric system is protecting the templates of the users that
are stored either in a central database or on smart cards. If a biometric template is compromised, it leads to
serious security and privacy threats because unlike passwords, it is not possible for a legitimate user to revoke
his biometric identifiers and switch to another set of uncompromised identifiers. One methodology for biometric
template protection is the template transformation approach, where the template, consisting of the features
extracted from the biometric trait, is transformed using parameters derived from a user specific password or
key. Only the transformed template is stored and matching is performed directly in the transformed domain.
In this paper, we formally investigate the security strength of template transformation techniques and define
six metrics that facilitate a holistic security evaluation. Furthermore, we analyze the security of two wellknown
template transformation techniques, namely, Biohashing and cancelable fingerprint templates based on
the proposed metrics. Our analysis indicates that both these schemes are vulnerable to intrusion and linkage
attacks because it is relatively easy to obtain either a close approximation of the original template (Biohashing)
or a pre-image of the transformed template (cancelable fingerprints). We argue that the security strength
of template transformation techniques must consider also consider the computational complexity of obtaining a
complete pre-image of the transformed template in addition to the complexity of recovering the original biometric
template.
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