Accuracy and Security Evaluation of Multi-Factor Biometric Authentication

Abstract

This paper aims to evaluate the security and accuracy of Multi-Factor Biometric Authentication (MFBA) schemes that are based on applying User-Based Transformations (UBTs) on biometric features. Typically, UBTs employ transformation keys generated from passwords/PINs or retrieved from tokens. In this paper, we not only highlight the importance of simulating the scenario of compromised transformation keys rigorously, but also show that there has been misevaluation of this scenario as the results can be easily misinterpreted. In particular, we expose the falsehood of the widely reported claim in the literature that in the case of stolen keys, authentication accuracy drops but remains close to the authentication accuracy of biometric only system. We show that MFBA systems setup to operate at zero (%) Equal Error Rates (EER) can be undermined in the event of keys being compromised where the False Acceptance Rate reaches unacceptable levels. We demonstrate that for commonly used recognition schemes the FAR could be as high as 21%, 56%, and 66% for iris, fingerprint, and face biometrics respectively when using stolen transformation keys compared to near zero (%) EER when keys are assumed secure. We also discuss the trade off between improving accuracy of biometric systems using additional authentication factor(s) and compromising the security when the additional factor(s) are compromised. Finally, we propose mechanisms to enhance the security as well as the accuracy of MFBA schemes.

Combining steganography and biometric cryptosystems for secure mutual authentication and key exchange

“…Random Orthonormal Projection (ROP) is a technique that uses random orthonormal matrices to project data points into other spaces while preserving distances. RP has been proposed as a secure transform for biometric templates [8], [9] to meet the revocability property for biometric-based authentication systems. An efficient 978-1-908320-20/9/$25.00©2013 IEEE method of generating orthonormal matrices was proposed by the authors in [8].…”

“…RP has been proposed as a secure transform for biometric templates [8], [9] to meet the revocability property for biometric-based authentication systems. An efficient 978-1-908320-20/9/$25.00©2013 IEEE method of generating orthonormal matrices was proposed by the authors in [8]. Let x be the feature vector of size n, A be an n Xn orthonormal random matrix, b is a random vector of size n, and P be a permutation matrix of size n, the transformation is given by…”

“…It has been shown in [8] that the transformation given in (1) enhances security while preserving the intra-class variation.…”

Privacy preserving, real-time and location secured biometrics for mCommerce authentication

“…Note that it is feasible to achieve perfect matching or 100% accuracy or a zero % Equal Error Rate (EER) when the ROP transformation keys are assumed to be secure. However, in this case fingerprint system suffers from a very high FAR when the ROP transformation key is compromised (see [18,19] for further details on performance evaluation for such systems). To produce a biometric key, there is a need to deal with the fuzziness of biometric samples resulting from the differences between the freshly captured fingerprint sample and the enrolled templates.…”

Feasibility study on authentication based keystroke dynamic over touch-screen devices

“…Most of authentication methods on mobile devices in general are only just a knowledge factor, like pass code. Many researches show that the result using multi-factor in the authentication process can provide a better result in the authentication mechanism due to the increasing of the security issue [1] [2].…”