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Authors: M. A. Haytom 1 ; C. Rosenberger 2 ; C. Charrier 2 ; C. Zhu 3 and C. Regnier 3

Affiliations: 1 Normandie Univ., UNICAEN, ENSICAEN, CNRS, GREYC, 14000 Caen, France, TestWe, 75003 Paris, France ; 2 Normandie Univ., UNICAEN, ENSICAEN, CNRS, GREYC, 14000 Caen, France ; 3 TestWe, 75003 Paris, France

Keyword(s): Personal Data, Biometric Authentication, Privacy Protection, Machine Learning.

Abstract: Distant learning is an alternative solution to education when the learner is far from the school or cannot attend courses for professional or medical reasons. The main objective of this work is to design a smart application of remote exams, using a multibiometric system combining face with deep learning and keystroke dynamics to verify the identity of the learner. Privacy protection is consider in this work as an important issue because many personal data are processed in the proposed solution. We consider in this paper experiments under real-life conditions to identify abnormal behaviours with confidence indicators. We show the system ability to make the correct decision while preserving learner’s privacy.

CC BY-NC-ND 4.0

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Paper citation in several formats:
Haytom, M.; Rosenberger, C.; Charrier, C.; Zhu, C. and Regnier, C. (2020). Identity Verification and Fraud Detection During Online Exams with a Privacy Compliant Biometric System. In Proceedings of the 17th International Joint Conference on e-Business and Telecommunications - SECRYPT; ISBN 978-989-758-446-6; ISSN 2184-7711, SciTePress, pages 451-458. DOI: 10.5220/0009874104510458

@conference{secrypt20,
author={M. A. Haytom. and C. Rosenberger. and C. Charrier. and C. Zhu. and C. Regnier.},
title={Identity Verification and Fraud Detection During Online Exams with a Privacy Compliant Biometric System},
booktitle={Proceedings of the 17th International Joint Conference on e-Business and Telecommunications - SECRYPT},
year={2020},
pages={451-458},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0009874104510458},
isbn={978-989-758-446-6},
issn={2184-7711},
}

TY - CONF

JO - Proceedings of the 17th International Joint Conference on e-Business and Telecommunications - SECRYPT
TI - Identity Verification and Fraud Detection During Online Exams with a Privacy Compliant Biometric System
SN - 978-989-758-446-6
IS - 2184-7711
AU - Haytom, M.
AU - Rosenberger, C.
AU - Charrier, C.
AU - Zhu, C.
AU - Regnier, C.
PY - 2020
SP - 451
EP - 458
DO - 10.5220/0009874104510458
PB - SciTePress