Abstract
The significant growth in users of e-learning
technologies and their use in courses has given rise to a major
concern over protecting them from misuse; a significant
concern is that of the potential for cheating or illicit assistance
during online examinations. This paper presents the
development of robust, flexible, transparent and continuous
authentication mechanism for e-assessments. To monitor the
exam taker and ensure that only the legitimate student is taking
the exam, the system offers a continuous user identification
employing multimodal biometrics; a security layer using an eye
tracker to record the student’s eye movement; and, speech
recognition to detect inappropriate communication. The focus
of this paper in particular is the development and evaluation of
3D facial authentication. An experiment has been conducted to
investigate the ability of the proposed platform to detect any
cheating attempts. During the experiment, participants'
biometric data, eye movement, and head movements have been
collected using custom software. The 3D camera also captured
the session using a built-in microphone and the system
recognized speech (employing a speech recognition algorithm).
51 participants participated in this experiment. The FRR of all
legitimate participants was 0 and 0.0063 in 2D and 3D facial
recognition modes respectively. Furthermore, three
participants were tasked with a series of eight scenarios that
map to typical misuse. The results of the FAR and FRR of five
of these threat scenarios in both 2D and 3D mode were 0 with
two cases exhibiting an FAR of 0.11 and 0.076 in the 2D mode.
Original language | English |
---|---|
Pages (from-to) | 796-802 |
Number of pages | 0 |
Journal | International Journal of Information and Education Technology |
Volume | 7 |
Issue number | 11 |
Early online date | Nov 2017 |
DOIs | |
Publication status | Published - Nov 2017 |