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Continuous verification using multimodal biometrics.

Terence Sim1, Sheng Zhang, Rajkumar Janakiraman

  • 1School of Computing, National University of Singapore, Singapore. tsim@comp.nus.edu.sg

IEEE Transactions on Pattern Analysis and Machine Intelligence
|February 15, 2007
PubMed
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This study introduces a multimodal biometrics system for continuous user verification, enhancing security in high-risk environments. It addresses limitations of traditional systems by employing face and fingerprint recognition for ongoing authentication.

Area of Science:

  • Computer Science
  • Biometrics
  • Cybersecurity

Background:

  • Conventional verification systems lack continuous monitoring for high-security needs.
  • Unauthorized use remains a risk in environments requiring persistent user authentication.

Purpose of the Study:

  • To present a multimodal biometrics system for continuous user verification.
  • To address the need for ongoing authentication in high-security environments.

Main Methods:

  • Developed a multimodal biometrics system using face and fingerprint modalities.
  • Proposed a theoretical framework for continuous verification.
  • Extended existing multimodal fusion theories for continuous authentication.

Main Results:

Related Experiment Videos

  • Demonstrated a system capable of continuously verifying logged-in users.
  • Identified unique challenges in multimodal fusion for continuous verification.
  • Proposed new performance metrics beyond traditional false accept/reject rates.

Conclusions:

  • Continuous verification is essential for high-security environments.
  • Multimodal biometrics offer a robust solution for ongoing user authentication.
  • New metrics are needed to accurately assess continuous verification systems.