TY - GEN
T1 - Privacy-preserving Biometric-driven Data for Student Identity Management
T2 - 29th ACM Conference on User Modeling, Adaptation and Personalization, UMAP 2021
AU - Fidas, Christos
AU - Belk, Marios
AU - Portugal, David
AU - Pitsillides, Andreas
N1 - Publisher Copyright:
© 2021 Owner/Author.
PY - 2021/6/21
Y1 - 2021/6/21
N2 - 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.
AB - 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.
KW - Biometrics
KW - Blockchain
KW - Privacy
KW - Security
KW - User Authentication
UR - http://www.scopus.com/inward/record.url?scp=85109218972&partnerID=8YFLogxK
U2 - 10.1145/3450614.3464470
DO - 10.1145/3450614.3464470
M3 - Conference contribution
AN - SCOPUS:85109218972
T3 - UMAP 2021 - Adjunct Publication of the 29th ACM Conference on User Modeling, Adaptation and Personalization
SP - 368
EP - 370
BT - UMAP 2021 - Adjunct Publication of the 29th ACM Conference on User Modeling, Adaptation and Personalization
PB - Association for Computing Machinery, Inc
Y2 - 21 June 2020 through 25 June 2020
ER -