IEEE Access (Jan 2022)

Evaluation of PPG Feature Values Toward Biometric Authentication Against Presentation Attacks

  • Shun Hinatsu,
  • Daisuke Suzuki,
  • Hiroki Ishizuka,
  • Sei Ikeda,
  • Osamu Oshiro

DOI
https://doi.org/10.1109/ACCESS.2022.3167667
Journal volume & issue
Vol. 10
pp. 41352 – 41361

Abstract

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In this study, we examined information leakage in photoplethysmogram (PPG)-based biometric authentication and assessed an attack against authentication based on the information leakage. Several approaches have been proposed to apply PPG to biometric authentication using a wearable device; however, there may be several attacks against PPG-based authentication. One of the attacks is a “presentation attack” (PA), which utilizes the information leakage originating from the various PPG measurement sites on a body. The PA records the victim’s PPG stealthily on non-genuine measurement sites and transmits it to the PPG sensor to break the authentication. We examined the information leakage and assessed the PA by evaluating feature values extracted from the PPG signals. We recorded the PPG signals of 12 participants on their fingertips and wrists. We compared the feature values extracted from the recorded PPG signals by computing the differences, correlation coefficients, and mutual information to examine the leakage of information required for the PPG-based authentication. We then assessed the feasibility of a PA based on existing PPG-based authentication algorithms and evaluated the contribution of each value to authentication and PA by computing the permutation importance of all feature values. The experimental results indicated that there might be information leakage and selection of feature values to reduce the feasibility of the PA up to 62.8 %.

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