Received April 27, 2021, accepted May 5, 2021, date of publication May 11, 2021, date of current version May 21, 2021. Digital Object Identifier 10.1109/ACCESS.2021.3079375 Online Student Authentication and Proctoring System Based on Multimodal Biometrics Technology MIKEL LABAYEN 1,3 , RICARDO VEA 1 , JULIÁN FLÓREZ 2 , (Member, IEEE), NAIARA AGINAKO 3 , AND BASILIO SIERRA 3 1 Smowltech, 20009 Donostia, Spain 2 Vicomtech Research Center, 20009 Donostia, Spain 3 Computer Sciences and Artificial Intelligence Department, University of the Basque Country, 20018 Donostia, Spain Corresponding author: Mikel Labayen (mikel.labayen@ehu.eus) This work was supported by the Spanish Ministry of Sciences, Research and Universities (Ministerio de Ciencia, Innovación y Universidades (MCIU)/Agencia Estatal de Investigación (AEI)/Fondo Europeo de Desarrollo Regional (FEDER), Unión Europea (UE)) under Grant RTC-2016-5711-7. ABSTRACT Identity verification and proctoring of online students are one of the key challenges to online learning today. Especially for online certification and accreditation, the training organizations need to verify that the online students who completed the learning process and received the academic credits are those who registered for the courses. Furthermore, they need to ensure that these students complete all the activities of online training without cheating or inappropriate behaviours. The COVID-19 pandemic has accelerated (abruptly in certain cases) the migration and implementation of online education strategies and consequently the need for safe mechanisms to authenticate and proctor online students. Nowadays, there are several technologies with different grades of automation. In this paper, we deeply describe a specific solution based on the authentication of different biometric technologies and an automatic proctoring system (system workflow as well as AI algorithms), which incorporates features to solve the main concerns in the market: highly scalable, automatic, affordable, with few hardware and software requirements for the user, reliable and passive for the student. Finally, the technological performance test of the large scale system, the usability- privacy perception survey of the user and their results are discussed in this work. INDEX TERMS Biometric authentication, cloud computing, computer vision, data science applications in education, distance education and online learning, machine learning, security, computer vision. I. INTRODUCTION There is no doubt that online learning has been gaining popularity throughout the past years. This phenomenon is not surprising given that online learning allows education institutes to operate at a lower cost and with greater reach- out to more students. Educational institutions are offering courses online to leverage the benefits of online learning. This is especially so since the advent of Massive Open Online Courses (MOOC). On the other hand, COVID-19 has been a challenge for traditional institutes offering face-to- face teaching, and these institutions have had to migrate (in a very short period of time) to a fully online education model The associate editor coordinating the review of this manuscript and approving it for publication was Tony Thomas. forced by the pandemic situation. However, online learning implementation presents challenges. E-learning has a serious deficiency, which is the lack of efficient mechanisms that assure user authentication, in the system login as well as throughout the session. Especially for online certification and accreditation, the training organiza- tions need to verify that the online learners who completed the learning process and received the academic credits are precisely those who registered for the courses. Inadequate methods of identity verification affect the reliability of cre- dentials and certification earned online. Without certainty of the authenticity of the online learner’s identity, the aspiration towards fully online education is stymied and the evaluation of the knowledge and skills obtained by the online learner is unreliable. In order to pre- vent compromising the credibility of online accreditation, 72398 This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see https://creativecommons.org/licenses/by/4.0/ VOLUME 9, 2021