A Multi-Biometric System for Continuous Student Authentication in E-Learning Platforms


In recent years, online courses have emerged as a new way to educate students in distance learning settings. However, as the demand increases, educational institutions are facing the challenge of how to prove that online students are who they claim to be during e-learning activities, especially exams. Human proctoring is a non-scalable approach which requires a person to monitor each student remotely. On the other hand, automated proctors tend to target a specific type of device and verify the students’ presence without considering their interaction with the e-learning platform. In this paper, we propose a device/interaction-agnostic multi-biometric system aimed at continuously and transparently verifying both the presence and the interaction. By performing a score-level fusion of different biometric responses (face, voice, touch, mouse, keystroke) based on the device used and the interaction carried out with it, the system is able to attest the student’s identity throughout the learning experience. In preliminary comparison with the existing approaches, our contribution has a good potential to provide a flexible and reliable support on a larger set of online experiences.