Proctoring Online Exam Using Eye Tracking

Yaqub, W; Mohanty, M; Suleiman, B

Proctoring Online Exam Using Eye Tracking

Yaqub, W Mohanty, M

Suleiman, B

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Publisher:: Scitepress
Publication Type:: Conference Proceeding
Citation:: Proceedings of the International Conference on Security and Cryptography, 2023, 1, pp. 738-745
Issue Date:: 2023-01-01

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Field	Value	Language
dc.contributor.author	Yaqub, W
dc.contributor.author	Mohanty, M https://orcid.org/0000-0002-0258-4586
dc.contributor.author	Suleiman, B
dc.date	2023-07-10
dc.date.accessioned	2024-07-01T22:36:48Z
dc.date.available	2024-07-01T22:36:48Z
dc.date.issued	2023-01-01
dc.identifier.citation	Proceedings of the International Conference on Security and Cryptography, 2023, 1, pp. 738-745
dc.identifier.isbn	9789897586668
dc.identifier.issn	2184-7711
dc.identifier.uri	http://hdl.handle.net/10453/179690
dc.description.abstract	Online proctoring is required for online teaching. Typically, third-party video-based crowd-sourced online proctoring solutions are being used for monitoring exam-takers (e.g., students). This approach, however, has privacy concerns as an exam-taker’s face is shown to the third-party provider. In this paper, we propose to address this concern using face hiding, and then monitoring the face hidden exam takers via eye (gaze) tracking. The eye tracking is used to detect if the exam-taker is reading from computer screen, e.g., from ChatGPT. The face is hidden by exposing the eyes such that eye tracking is possible.
dc.language	en
dc.publisher	Scitepress
dc.relation.ispartof	Proceedings of the International Conference on Security and Cryptography
dc.relation.ispartof	International Conference on Security and Cryptography
dc.relation.isbasedon	10.5220/0012120600003555
dc.rights	info:eu-repo/semantics/openAccess
dc.title	Proctoring Online Exam Using Eye Tracking
dc.type	Conference Proceeding
utslib.citation.volume	1
utslib.location.activity	Rome, Italy
pubs.organisational-group	University of Technology Sydney
pubs.organisational-group	University of Technology Sydney/Faculty of Science
pubs.organisational-group	University of Technology Sydney/Strength - CFS - Centre for Forensic Science
pubs.organisational-group	University of Technology Sydney/Faculty of Science/School of Mathematical and Physical Sciences
utslib.copyright.status	open_access	*
pubs.consider-herdc	false
dc.rights.license	This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (CC BY-NC-ND 4.0). To view a copy of this license, visit https://creativecommons.org/licenses/by-nc-nd/4.0/
dc.date.updated	2024-07-01T22:36:45Z
pubs.finish-date	2023-07-12
pubs.publication-status	Published
pubs.start-date	2023-07-10
pubs.volume	1

Abstract:

Online proctoring is required for online teaching. Typically, third-party video-based crowd-sourced online proctoring solutions are being used for monitoring exam-takers (e.g., students). This approach, however, has privacy concerns as an exam-taker’s face is shown to the third-party provider. In this paper, we propose to address this concern using face hiding, and then monitoring the face hidden exam takers via eye (gaze) tracking. The eye tracking is used to detect if the exam-taker is reading from computer screen, e.g., from ChatGPT. The face is hidden by exposing the eyes such that eye tracking is possible.

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http://hdl.handle.net/10453/179690