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FR-CAPTCHA: CAPTCHA based on recognizing human faces.

Gaurav Goswami1, Brian M Powell2, Mayank Vatsa1

  • 1Indraprastha Institute of Information Technology, Delhi, India.

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Summary
This summary is machine-generated.

This study introduces FR-CAPTCHA, a novel Turing test using face recognition to differentiate humans from bots. FR-CAPTCHA offers improved accuracy and accessibility over traditional text-based challenges.

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Area of Science:

  • Computer Science
  • Human-Computer Interaction
  • Biometrics

Background:

  • Traditional Completely Automated Public Turing tests to tell Computers and Humans Apart (CAPTCHA) rely on distorted text, posing challenges for users and bots.
  • Existing CAPTCHA systems exhibit language dependencies and varying difficulty levels, impacting user experience and security.
  • There is a need for more accessible and robust Turing tests that overcome the limitations of text-based CAPTCHAs.

Purpose of the Study:

  • To propose and evaluate FR-CAPTCHA, a novel Turing test utilizing face recognition for human-computer differentiation.
  • To assess the effectiveness of FR-CAPTCHA against automated attacks and compare its performance with existing CAPTCHA methods.
  • To develop a more accessible and inclusive CAPTCHA solution.

Main Methods:

  • Developed FR-CAPTCHA, a system that requires users to identify matching pairs of human faces within an image.
  • Employed face recognition algorithms as the core mechanism for the Turing test.
  • Evaluated FR-CAPTCHA's human accuracy and robustness against automated bot attacks.

Main Results:

  • FR-CAPTCHA achieved a human accuracy rate of 94%.
  • The proposed face recognition CAPTCHA demonstrated robustness against automated attacks.
  • FR-CAPTCHA mitigates issues of language dependency and demographic inconvenience found in text-based CAPTCHAs.

Conclusions:

  • FR-CAPTCHA presents a viable and effective alternative to traditional text-based CAPTCHAs.
  • Face recognition offers a promising approach for developing more secure and user-friendly Turing tests.
  • The proposed system enhances accessibility and security in human-computer differentiation.