A Comprehensive Survey of Context-Aware Continuous Implicit Authentication in Online Learning Environments

User authentication is crucial in the digital learning environment to preserve the integrity and reliability of the learning process. Implicit authentication using biometrics has been proposed to improve the user experience while resolving the issues that password dominant authentication faces. Impl...

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Bibliographic Details
Main Authors: Riseul Ryu, Soonja Yeom, David Herbert, Julian Dermoudy
Format: Article
Language:English
Published: IEEE 2023-01-01
Series:IEEE Access
Subjects:
Online Access:https://ieeexplore.ieee.org/document/10061213/
Description
Summary:User authentication is crucial in the digital learning environment to preserve the integrity and reliability of the learning process. Implicit authentication using biometrics has been proposed to improve the user experience while resolving the issues that password dominant authentication faces. Implicit authentication does not require explicit user actions as it is a background process that implicitly acquires a user’s identifying information through sensors embedded within the authenticating devices. To accommodate a variety of user contexts, context-aware implicit authentication has gained attention—especially in the mobile device domain—but it has not been fully explored in digital learning environments. This study is motivated to determine how implicit authentication can observe students’ behaviour without causing disruption to their learning activity. The study provides a structured systematic review of the existing literature to identify and discuss the structure of context-aware continuous implicit authentication systems and future directions. The study found that requirements in the future will be: 1) to consider diverse authenticators to cover all possible user interactions with online learning environments, including coverage of course participants not engaged with online exams; 2) to investigate template adaptation to overcome template ageing issues with biometrics; and 3) to explore evaluation approaches of context-aware implicit authentication systems.
ISSN:2169-3536