Abstract

Nowadays, online learning or e-learning has become increasingly popular and evolved. Many academic institutions use the Learning Management System (LMS) as a medium for delivering e-learning. A vital feature in such a system is the electronic examination (e-exam), where verifying student’s authentic competence is a challenge. This paper aims to present countermeasures for impersonation attacks. This research was a more focused effort and a continuation of previously owned one and many others found in works of literature. The method of protection is presented in the form of an attack-defense tree model.

Highlights

  • Educational institutions use online learning systems to deliver learning materials

  • Concerns have increased in the integrity of the online exam process, which is one of the crucial activities in online learning [1]

  • According to [4], there are seven types of e-exam cheating attacks [5], which are: 1) Impersonation 2) Assistance/collaboration 3) Plagiarism 4) Using aids not allowed for the exam 5) Time violations 6) Lying to proctors 7) Smuggling out the exam questions after the exam

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Summary

Introduction

Educational institutions use online learning systems to deliver learning materials Through these systems, students can interact and perform learning activities from remote locations online. Students can interact and perform learning activities from remote locations online Many educational institutions adopt this system because of its greater flexibility and lower cost than other systems Another advantage is that even though their code is iJET ‒ Vol 15, No 19, 2020. To study attacks and defenses that can be used in e-exams, the researchers developed several models. Researchers made the ADTrees formalization done by expanding the attack tree in two methods [3]. The process of extending this node is utilizing ADTools by conducting study literature on research that has topics related to the authentication method in the e-exam. Additional objects from each literature are designated as new subnodes

Attack-Defense Tree e-Exam System
Cheating Attack-Defense Tree
Impersonation Attack-Defense Tree Extended
Biometric
Conclusion
Authors
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