人工智能辅助的基于风险的双因素认证方法(AIA-RB-2FA)

Shiburaj Pappu, Dhanashree Kangane, Varsha Shah, Junaid Mandwiwala
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引用次数: 0

摘要

身份验证是任何安全系统中允许访问受限制资源的重要步骤。在本文中,我们提出了一种新的人工智能辅助的基于风险的双因素认证方法。我们从使用中的现有系统的细节开始,然后比较两种系统,即:双因素身份验证(2FA),基于风险的双因素身份验证(RB-2FA),然后是我们提出的AIA-RB-2FA方法。该方法首先在用户每次登录时记录用户特征,并从用户行为中学习。一旦记录了足够的数据,可以训练人工智能模型,系统就会开始监控每次登录尝试,并预测用户是否是他们试图访问的账户的所有者。如果不是,那么我们就退回到2FA。
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AI-Assisted Risk Based Two Factor Authentication Method (AIA-RB-2FA)
Authentication, forms an important step in any security system to allow access to resources that are to be restricted. In this paper, we propose a novel artificial intelligence-assisted risk-based two-factor authentication method. We begin with the details of existing systems in use and then compare the two systems viz: Two Factor Authentication (2FA), Risk-Based Two Factor Authentication (RB-2FA) with each other followed by our proposed AIA-RB-2FA method. The proposed method starts by recording the user features every time the user logs in and learns from the user behavior. Once sufficient data is recorded which could train the AI model, the system starts monitoring each login attempt and predicts whether the user is the owner of the account they are trying to access. If they are not, then we fallback to 2FA.
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