Real-time continuous iris recognition for authentication using an eye tracker
Author(s): Kenrick Mock, Bogdan Hoanca, Justin Weaver, Mikal Milton

Date: October 2012
Publication: Proceedings of the 2012 ACM Conference on Computer and Communications Security, CCS '12
Page(s): 1007 - 1009
Publisher: ACM
Source 1: http://www.math.uaa.alaska.edu/~afkjm/papers/Iris-CCS2012.pdf
Source 2: http://dx.doi.org/10.1145/2382196.2382307 - Subscription or payment required

Abstract or Summary:
The majority of today's authentication systems, including password and fingerprint scanners, are based on one-time, static authentication methods. A continuous, real-time authentication system opens up the possibility for greater security, but such a system must be unobtrusive and secure. In this work we studied whether a commercial eye tracker can be used for unobtrusive, continuous, real-time user authentication via iris recognition. In a user study, all 37 participants could be authenticated with 11% equal error rate (EER). For 14 of the 37 users, iris occlusion was sufficiently small to authenticate with 9% EER. When classified using a k-nearest neighbors algorithm and only the right iris, the same data set allowed 100% accuracy for k = 3. Although these error rates are too high for standalone use, iris recognition via an eye tracker might enable real-time continuous authentication when combined with other more reliable authentication means (e.g., a password). As eye trackers become widely available their capabilities for multiple factor, continuous authentication will become compelling.



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