AirAuth: Evaluating In-Air Hand Gestures for Authentication
Date: September 2014
Publication: Proceedings of the 16th International Conference on Human-Computer Interaction with Mobile Devices & Services, MobileHCI '14
Source 1: http://dl.acm.org/authorize?N89508
Source 2: http://www.fxpal.com/publications/airauth-evaluating-in-air-hand-gestures-for-authentication.pdf
Abstract or Summary:
Secure authentication with devices or services that store sensitive and personal information is highly important. However, traditional password and pin-based authentication methods compromise between the level of security and user experience. AirAuth is a biometric authentication technique that uses in-air gesture input to authenticate users. We evaluated our technique on a predefined (simple) gesture set and our classifier achieved an average accuracy of 96.6% in an equal error rate (EER-)based study. We obtained an accuracy of 100% when exclusively using personal (complex) user gestures. In a further user study, we found that AirAuth is highly resilient to video-based shoulder surfing attacks, with a measured false acceptance rate of just 2.2%. Furthermore, a longitudinal study demonstrates AirAuthís repeatability and accuracy over time. AirAuth is relatively simple, robust and requires only a low amount of computational power and is hence deployable on embedded or mobile hardware. Unlike traditional authentication methods, our systemís security is positively aligned with user-rated pleasure and excitement levels. In addition, AirAuth attained acceptability ratings in personal, office, and public spaces that are comparable to an existing stroke-based on-screen authentication technique. Based on the results presented in this paper, we believe that AirAuth shows great promise as a novel, secure, ubiquitous, and highly usable authentication method.
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