Continuous Verification Using Multimodal Biometrics

  • Sheng Zhang
  • Rajkumar Janakiraman
  • Terence Sim
  • Sandeep Kumar
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3832)

Abstract

In this paper we describe a system that continually verifies the presence/participation of a logged-in user. This is done by integrating multimodal passive biometrics in a Bayesian framework that combines both temporal and modality information holistically, rather than sequentially. This allows our system to output the probability that the user is still present even when there is no observation.

Our implementation of the continuous verification system is distributed and extensible, so it is easy to plug in additional asynchronous modalities, even when they are remotely generated. Based on real data resulting from our implementation, we find the results to be promising.

Keywords

Face Image Fusion Method Legitimate User State Transition Model Security Administrator 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Sheng Zhang
    • 1
  • Rajkumar Janakiraman
    • 1
  • Terence Sim
    • 1
  • Sandeep Kumar
    • 1
  1. 1.School of ComputingNational University of SingaporeSingapore

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