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Distinguishability of keystroke dynamic template.

Napa Sae-Bae1, Nasir Memon2

  • 1Computer Science Department, Faculty of Science, Srinakharinwirot University, Bangkok, Thailand.

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|January 21, 2022
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Summary
This summary is machine-generated.

This study introduces a new metric to assess keystroke dynamics template quality, aiming to improve security in behavioral biometric authentication systems. The metric predicts false acceptance rates, enhancing user verification accuracy.

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Area of Science:

  • Computer Science
  • Cybersecurity
  • Biometrics

Background:

  • Keystroke dynamics authentication security varies due to differences in user template quality.
  • High intra-user variation in keystroke dynamics leads to higher false acceptance rates (FAR).

Purpose of the Study:

  • To propose a metric for quantifying the quality of keystroke dynamic templates.
  • To reflect the verification performance of individual templates in terms of FAR.

Main Methods:

  • Developed a metric derived from statistical information of user-specific feature variations.
  • Evaluated the metric on two public keystroke dynamics datasets (CMU and Web-Based Benchmark).
  • Tested the metric's effectiveness using multiple classifiers.

Main Results:

  • The proposed metric effectively indicates the false acceptance rate (FAR) of individual keystroke dynamic templates.
  • Experimental results demonstrate the metric's reliability across different classifiers and datasets.
  • The metric shows a non-decreasing property with the addition of new features to a template.

Conclusions:

  • The developed metric can serve as a valuable indicator of template quality in keystroke dynamics authentication.
  • Implementing this metric can enhance the overall security of user authentication systems.
  • This approach addresses the challenge of variable security levels in keystroke dynamics biometrics.