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首页> 外文期刊>Systems Journal, IEEE >Leveraging Biometrics for User Authentication in Online Learning: A Systems Perspective
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Leveraging Biometrics for User Authentication in Online Learning: A Systems Perspective

机译:利用生物识别技术进行在线学习中的用户身份验证:系统角度

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With the rapid proliferation of online learning, students are increasingly demanding easy and flexible access to learning content at a time and location of their choosing. In these environments, remote users connecting via the public Internet or other unsecure networks must be authenticated prior to being granted access to sensitive content such as tests or personal/private records. Today, the overwhelming majority of online learning systems rely on weak authentication mechanisms to verify the identity of remote users only at the start of each session. One-time authentication using password, personal identification number (PIN), or even hardware tokens is clearly inadequate in that it cannot defend against insider attacks including remote user impersonation or illegal sharing or disclosure of these authentication secrets. As such, these methods are entirely unsuitable for circumstances where the outcome of an online assessment or a course of study is the granting of a formal degree, professional certification, or qualification or requalification for a particular skill or function. This paper examines the problem of remote authentication in online learning environments and explores the challenges and options of using biometric technology to defend against user impersonation attacks by certifying the presence of the user in front of the computer, at all times. It also leverages a 5-step process as the basis for a systems approach to ensuring that the proposed solution will meet the critical remote authentication assurance requirements. The process and systems approach employed here are generic, and can be exploited when introducing biometric-enabled authentication solutions to other applications and business domains. The paper concludes by presenting a biometrics-based client-server architecture for continuous user authentication in e-learning environments.
机译:随着在线学习的迅速普及,学生越来越要求在他们选择的时间和地点方便且灵活地访问学习内容。在这些环境中,必须先对通过公用Internet或其他不安全网络连接的远程用户进行身份验证,然后才能授予对敏感内容(如测试或个人/私人记录)的访问权限。如今,绝大多数在线学习系统仅在每次会话开始时就依靠弱认证机制来验证远程用户的身份。使用密码,个人识别码(PIN)或什至是硬件令牌的一次性身份验证显然是不充分的,因为它无法防御内部攻击,包括远程用户假冒或非法共享或泄露这些身份验证秘密。因此,这些方法完全不适合在线评估或学习课程的结果是授予正式学位,专业证书或对特定技能或功能的资格或再认证的情况。本文研究了在线学习环境中的远程身份验证问题,并探讨了使用生物识别技术始终通过验证用户在计算机前的存在来防御用户假冒攻击的挑战和选择。它还利用5步过程作为系统方法的基础,以确保所提出的解决方案将满足关键的远程身份验证保证要求。这里采用的过程和系统方法是通用的,并且在将启用生物识别功能的身份验证解决方案引入其他应用程序和业务领域时可以加以利用。本文最后提出了一种基于生物特征的客户端-服务器体系结构,用于在电子学习环境中进行连续的用户身份验证。

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