击键力学

A. V. S. Kumar, Menal Rathi
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引用次数: 2

摘要

在线学习完全改变了学生的学习方式。在线测试和测验在在线学习中发挥着重要作用,为教师提供准确的结果。但是,学习者在在线考试中使用不同的方法作弊,例如打开浏览器搜索答案或在本地驱动器中搜索文档等。一旦他们登录并参加在线考试,他们就不会被认证。参加在线考试的学生的身份验证使用了不同的技术,如音频或视频监控系统,指纹或虹膜识别等。基于击键动态的身份验证(KDA)方法是一种基于行为生物特征的身份验证模型,已成为用户身份验证领域的研究热点。本章提出了使用KDA作为在线考试用户认证的解决方案,并详细介绍了KDA的过程、影响KDA性能的因素、它们在不同领域的应用,以及一些基于击键动态的在线考试用户认证数据集。
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Keystroke Dynamics
Online learning has entirely transformed the way of learning by the students. Online tests and quizzes play an important role in online learning, which provides accurate results to the instructor. But, the learners use different methods to cheat during online exams such as opening a browser to search for the answer or a document in the local drive, etc. They are not authenticated once they login and progress to attend the online exams. Different techniques are used in authenticating the students taking up the online exams such as audio or video surveillance systems, fingerprint, or iris recognition, etc. Keystroke dynamics-based authentication (KDA) method, a behavioral biometric-based authentication model has gained focus in authenticating the users. This chapter proposes the usage of KDA as a solution to user authentication in online exams and presents a detailed review on the processes of KDA, the factors that affect the performance of KDA, their applications in different domains, and a few keystroke dynamics-based datasets to authenticate the users during online exams.
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Mitigation of Cheating in Online Exams Biometric Authentication Techniques and E-Learning Biometric Authentication Techniques and Its Future Keystroke Dynamics Keystroke Dynamics in E-Learning
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