Learning a Policy for Gesture-Based Active Multi-touch Authentication

Raquel Torres Peralta, Anton Rebguns, Ian R. Fasel, Kobus Barnard

Research output: Other contributionpeer-review

Abstract

Multi-touch tablets 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 when drawing a combination of one-stroke gestures following two different policies, one fixed for all users and the other selected by a model of control to maximize the expected long-term information gain. 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.

Original languageAmerican English
PublisherSpringer Verlag
Number of pages59
ISBN (Print)978-3-642-39344-0
ISBN (Electronic)978-3-642-39345-7
DOIs
StatePublished - 2013

Keywords

  • Support Vector Machine
  • Latent Dirichlet Allocation
  • Good Policy
  • Dirichlet Distribution
  • Intermediate Representation

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