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.
Biometrics is rapidly gaining acceptance as the technology that can meet the ever increasing need for security in critical applications. Biometric systems automatically recognize individuals based on their physiological and behavioral characteristics. Hence, the fundamental requirement of any biometric recognition system is a human trait having several desirable properties like universality, distinctiveness, permanence, collectability, acceptability, and resistance to circumvention. However, a human characteristic that possesses all these properties has not yet been identified. As a result, none of the existing biometric systems provide perfect recognition and there is a scope for improving the performance of these systems. Although characteristics like gender, ethnicity, age, height, weight and eye color are not unique and reliable, they provide some information about the user. We refer to these characteristics as "soft" biometric traits and argue that these traits can complement the identity information provided by the primary biometric identifiers like fingerprint and face. This paper presents the motivation for utilizing soft biometric information and analyzes how the soft biometric traits can be automatically extracted and incorporated in the decision making process of the primary biometric system. Preliminary experiments were conducted on a fingerprint database of 160 users by synthetically generating soft biometric traits like gender, ethnicity, and height based on known statistics. The results show that the use of additional soft biometric user information significantly improves (approximately 6%) the recognition performance of the fingerprint biometric system.
Conference Committee Involvement (3)
Biometric Technology for Human Identification IX
23 April 2012 | Baltimore, Maryland, United States
Biometric Technology for Human Identification VIII
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