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    Recognizing User Identity by Touch on Tabletop Displays: An Interactive Authentication Method

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    Author
    Torres Peralta, Raquel
    Issue Date
    2012
    Keywords
    Multitouch
    User Recognition
    Computer Science
    Authentication
    Machine Learning
    Advisor
    Barnard, Kobus
    
    Metadata
    Show full item record
    Publisher
    The University of Arizona.
    Rights
    Copyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author.
    Embargo
    Release after 19-Dec-2013
    Abstract
    Multi-touch tablets allow users to interact with computers through intuitive, natural gestures and direct manipulation of digital objects. One advantage of these devices is that they can offer a large, collaborative space where several users can work on a task at the same time. However the lack of privacy in these situations makes standard password-based authentication easily compromised. This work presents a new gesture-based authentication system based on users' unique signature of touch motion. This technique has two key features. First, at each step in authentication the system prompts the user to make a specific gesture selected to maximize the expected long-term information gain. Second, each gesture is integrated using a hierarchical probabilistic model, allowing the system to accept or reject a user after a variable number of gestures. This touch-based approach would allow the user to accurately authenticate without the need to cover their hand or look over their shoulder. This method has been tested using a set of samples collected under real-world conditions in a business office, with a touch tablet that was used on a near daily basis by users familiar with the device. Despite the lack of sophisticated, high-precision equipment, the system is able to achieve high user recognition accuracy with relatively few gestures, demonstrating that human touch patterns have a distinctive signature" that can be used as a powerful biometric measure for user recognition and personalization.
    Type
    text
    Electronic Dissertation
    Degree Name
    Ph.D.
    Degree Level
    doctoral
    Degree Program
    Graduate College
    Computer Science
    Degree Grantor
    University of Arizona
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