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    Machine and Deep Learning Applications to Mouse Dynamics for Continuous User Authentication

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    File(s)
    SiddiquiSpr22.pdf (714.8Kb)
    Date
    2022-04
    Author
    Siddiqui, Nyle
    Advisor(s)
    Dave, Rushit
    Metadata
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    Abstract
    Static authentication methods, like passwords and PINs, authenticate a user once and only once. Continually authenticating a user even after initial access can drastically increase account security against imposters. Unique behaviors, such as mouse movements, are distinct and varied enough between humans to be irreproducible. This makes them a viable biometric to utilize for user authentication. Machine and deep learning have exploded in popularity due to their superior ability to process large amounts of data. We train and evaluate three machine learning and three deep learning algorithms on our own novel mouse dynamics dataset.
    Subject
    Machine learning
    Authentication
    Computer security
    Posters
    Department of Computer Science
    Permanent Link
    http://digital.library.wisc.edu/1793/85152
    Type
    Presentation
    Description
    Color poster with text, images and charts.
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    • CERCA

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