Mr. Abhishek Nagar Profile

Abhishek Nagar

at Michigan State Univ

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Proceedings Article | 28 January 2010 Paper

Alignment and bit extraction for secure fingerprint biometrics

A. Nagar, S. Rane, A. Vetro

Proceedings Volume 7541, 75410N (2010) https://doi.org/10.1117/12.839130

KEYWORDS: Biometrics, Binary data, Feature extraction, Databases, Image filtering, Information security, Fingerprint recognition, Sensors, Computer security, Image enhancement

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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.

Proceedings Article | 28 January 2010 Paper

Biometric template transformation: a security analysis

Abhishek Nagar, Karthik Nandakumar, Anil Jain

Proceedings Volume 7541, 75410O (2010) https://doi.org/10.1117/12.839976

KEYWORDS: Biometrics, Biological research, Information security, Computer security, Databases, Iris, Binary data, Feature extraction, Bismuth, IRIS Consortium

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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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