NDLI: Multi-factor biometrics for authentication: a false sense of security

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Multi-factor biometrics for authentication: a false sense of security

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Multi-factor biometrics for authentication: a false sense of security

Content Provider	ACM Digital Library
Author	Jassim, Sabah Al-Assam, Hisham Sellahewa, Harin
Abstract	Multi-factor biometric authentications have been proposed recently to strengthen security and/or privacy of biometric systems in addition to enhancing authentication accuracy. An important approach to multi-factor biometric authentication is to apply User-Based Transformations (UBTs) on biometric features. Typically, UBTs rely on generating user-based transformation keys from a password/PIN or retrieved from a token. One significant advantage of employing UBTs is its ability to achieve zero or near zero Equal Error Rate (EER) i.e. a clear separation of genuine and imposter distributions. However, the effect of compromised transformation keys on authentication accuracy has not been tested rigorously. In this paper, we challenge the myth that has been reported in the literature that in the case of stolen transformation key(s), accuracy drops but remains close to the accuracy of biometric only system. Moreover, we shall show that a multi-factor authentication system setup to operate at a zero EER has a serious security lapse in the event of stolen or compromised keys. In such a scenario, the False Acceptance Rate (FAR) of the system reaches unacceptable levels. We shall demonstrate this by experiments conducted on face and fingerprint biometrics, and show that an imposter with a stolen key needs no more than two attempts on average to be falsely accepted by the biometric system.
Starting Page	81
Ending Page	88
Page Count	8
File Format	PDF
ISBN	9781450302869
DOI	10.1145/1854229.1854246
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2010-09-09
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Cancellable biometrics Face recognition Authentication Fingerprint recognition Multi-factor biometrics Security analysis
Content Type	Text
Resource Type	Article

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