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OdorTAM: Technology Acceptance Model for Biometric Authentication System Using Human Body Odor

Author

Listed:
  • Sameena Naaz

    (Department of Computer Science and Engineering, School of Engineering Sciences and Technology, Jamia Hamdard, New Delhi 110062, India)

  • Sarah Ali Khan

    (Department of Computer Science and Engineering, School of Engineering Sciences and Technology, Jamia Hamdard, New Delhi 110062, India)

  • Farheen Siddiqui

    (Department of Computer Science and Engineering, School of Engineering Sciences and Technology, Jamia Hamdard, New Delhi 110062, India)

  • Shahab Saquib Sohail

    (Department of Computer Science and Engineering, School of Engineering Sciences and Technology, Jamia Hamdard, New Delhi 110062, India)

  • Dag Øivind Madsen

    (USN School of Business, University of South-Eastern Norway, 3511 Hønefoss, Norway)

  • Asad Ahmad

    (Department of Management, School of Management and Business Studies, Jamia Hamdard, New Delhi 110062, India)

Abstract

Body odor is a biometric feature unique to each individual, and it can be used for authentication. However, decision makers must learn about the users’ level of acceptance of this technology, as well as their thoughts on the system’s features and procedures. In this study, a technology acceptance model (TAM) for body-odor-based biometric techniques named OdorTAM was proposed and validated. An English language questionnaire was developed in a web-based, easy-to-read format on Google Forms. The survey consisted of 19 questions, and 150 responses were received. Statistical analysis of the responses was carried out, and it was found that all the hypotheses were supported. Therefore, the OdorTAM model appears to be satisfactory. To this end, we posit that a body-odor-based biometric technique can be one of the alternatives for authentication, and it can also be used along with some other techniques for improved security. The study contributes to the literature on consumers’ understanding of biometric technologies, in particular odor detection, which has received relatively less attention in extant research.

Suggested Citation

  • Sameena Naaz & Sarah Ali Khan & Farheen Siddiqui & Shahab Saquib Sohail & Dag Øivind Madsen & Asad Ahmad, 2022. "OdorTAM: Technology Acceptance Model for Biometric Authentication System Using Human Body Odor," IJERPH, MDPI, vol. 19(24), pages 1-17, December.
    • Handle: RePEc:gam:jijerp:v:19:y:2022:i:24:p:16777-:d:1002909
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    References listed on IDEAS

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