Use of Biometrics in Mobile Identity Credentials White Paper

Pages: 5 (1429 words)  ·  Bibliography Sources: 8  ·  File: .docx  ·  Level: Corporate/Professional  ·  Topic: Computers - Technology  ·  Written: October 20, 2019

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Biometric System Convenience

In as far as convenience is concerned, there are three factors that ought to be highlighted. The first is ease of use. This is particularly the case given that unlike was the case a few decades ago, mobile phones have become widely used and are carried almost everywhere by their owners. Thus, with regard to the use of biometrics in mobile identity credentials, smartphones add to the convenience aspect. Next, relying on biometric authentication – specifically facial recognition in this case – is a rather effective way of preventing fraud and impersonation. This is particularly the case given that each person has unique biometric features which when utilized in the correct context and with the appropriate systems and processes in place could come in handy in the prevention of fraud and instances of impersonation. There is also the key, and related, factor of identity assurance. In this case, biometric authentication is far more effective than traditional identity assurance methods (Cristiani, Prati, and Lanz, 2019). Thus, thanks to face-based biometric authentication, it is possible to tell whether the person of interest is indeed whom they claim to be. It should also be noted that traditional credentials such as cards could be stolen, misplaced, or lost. A person’s biometric features, as MCGuire and Holt (2017) observe, are always with them and thus they can neither be lost, nor stolen, or misplaced. However, in the final analysis, it should be noted that there is need to maintain healthy balance between convenience, security and privacy.

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Application of Biometric Systems

White Paper on Use of Biometrics in Mobile Identity Credentials Assignment

In comparison to cards credential, there are various concerns that ought to be highlighted in relation to biometric systems. To begin with, the reissuance or revocation of biometric traits cannot be undertaken if and when the said traits are compromised. This is to say that if I were to have my biometrics compromised (i.e. the very valuable fingerprint I have shared), replacement would not be done like is the case when a password is stolen. The fact that there are other systems that utilize this particular biometric could make things worse. Secondly, it should be noted that after all, some biometric traits are not that well-secured. This is more so the case given that some, like fingerprints, could be left on surfaces.

There are various security concerns and threats linked in one way or another to specific attack points that ought to be mentioned. These include: genuine users denied system access by way of the continuous injection of samples; modification of the query credentials with an intention of obtaining the matching score desired; biometric signal interception with an intention of replaying it back to the system; acquisition or procurement of the primary biometric templates; spoofing attacks etc.

There are various countermeasures that could be undertaken in the light of the concerns highlighted above. As it has been pointed out elsewhere in this text, in seeking to prevent fake biometric attacks, the relevance of liveness detection cannot be overstated. In this case, the key feature is the determination as to whether or not the credentials presented could be attributed to a live person. As Guo and Wechsler (2017) point out, various hardware and software solutions have been developed on this front. The perspiration property or attribute has been proposed to, for instance, differentiate live from rubber/’unlive’ thumbs. It is also important to note that the biometric template protection could come in handy in this regard.

References
  1. Bhatia, R. (2013). Biometrics and Face Recognition Techniques. International Journal of Advanced Research in Computer Science and Software Engineering, 3(5), 93-99.
  2. Cristiani, M., Prati, A. & Lanz, O. (Eds). (2019). New Trends in Image Analysis and Processing - ICIAP 2019. Springer.
  3. Gelb, A. & Cark, J. (2013). Identification for Development: The Biometrics Revolution. Retrieved from https://www.cgdev.org/sites/default/files/1426862_file_Biometric_ID_for_Development.pdf
  4. Guo, G. & Wechsler, H. (2017). Mobile Biometrics. Mason, OH: Institution of Engineering and Technology.
  5. KPMG (2019). Biometric Authentication. Retrieved from https://home.kpmg/xx/en/home/insights/2018/02/biometric-authentication.html
  6. Marcel, S., Nixon, M.S. & Ferrez, J. (2019). Handbook of Biometric Anti-spoofing: Presentation Attack Detection (2nd ed.). New York, NY: Springer.
  7. McGuire, M.R. & Holt, T.J. (2017). The Routledge Handbook of Technology, Crime and Justice. New York, NY: Taylor & Francis.
  8. Pavlakis,… [END OF PREVIEW] . . . READ MORE

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