143519 - Continuous multibiometric authentication for online exam with machine learning.pdf (437.46 kB)
Continuous multibiometric authentication for online exam with machine learning
conference contribution
posted on 2023-05-23, 14:57 authored by Riseul RyuRiseul Ryu, Soonja YeomSoonja Yeom, Kim, S-HMultibiometric authentication has been received great attention over the past decades with the growing demand of a robust authentication system. Continuous authentication system verifies a user continuously once a person is login in order to prevent intruders from the impersonation. In this study, we propose a continuous multibiometric authentication system for the identification of the person during online exam using two modalities, face recognition and keystrokes. Each modality is separately processed to generate matching scores, and the fusion method is performed at the score level to improve the accuracy. The EigenFace and support vector machine (SVM) approach are applied to the facial recognition and keystrokes dynamic accordingly. The matching score calculated from each modality is combined using the classification by the decision tree with the weighted sum after the score is split into three zones of interest.
History
Publication title
Proceedings of the 2020 Australasian Conference on Information SystemsPagination
1-7Department/School
School of Information and Communication TechnologyPublisher
Association for Information SystemsPlace of publication
United StatesEvent title
2020 Australasian Conference on Information SystemsEvent Venue
Victoria University of Wellington, New ZealandDate of Event (Start Date)
2020-12-01Date of Event (End Date)
2020-12-04Rights statement
Copyright 2019 authors. This is an open-access article licensed under a Creative Commons Attribution-NonCommercial 3.0 New Zealand, which permits non-commercial use, distribution, and reproduction in any medium, provided the original author and ACIS are credited.Repository Status
- Open