Privacy-preserving Biometric-driven Data for Student Identity Management: Challenges and Approaches

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Abstract

Biometric technologies are being considered lately for student identity management in Higher Education Institutions, as they provide several advantages over the traditional knowledge-based and token-based authentication methods, i.e., biometrics provide high security entropies, convenience and a sense of technological modernity to the end-users. While biometric technologies have many benefits from both a security and usability point of view, still there is a need for innovative user identity management solutions that continuously identify and authenticate students during academic and teaching activities. In addition, biometrics entail several threats and weaknesses with regards to the privacy of data stored about the user, which negatively affect the user acceptance and the wider adoption of biometrics due to regulatory and legal issues. In this paper, we refer to our ongoing research on intelligent and continuous online student identity management for improving security and trust in European Higher Education Institutions. We further highlight based on the literature, existing challenges, threats and state-of-the-art approaches with regards to preserving the privacy of biometric-driven data.

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APA

Fidas, C., Belk, M., Portugal, D., & Pitsillides, A. (2021). Privacy-preserving Biometric-driven Data for Student Identity Management: Challenges and Approaches. In UMAP 2021 - Adjunct Publication of the 29th ACM Conference on User Modeling, Adaptation and Personalization (pp. 368–370). Association for Computing Machinery, Inc. https://doi.org/10.1145/3450614.3464470

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