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Two-Factor Authentication Using Leap Motion and Numeric Keypad

机译:使用飞跃运动和数字小键盘进行两要素身份验证

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摘要

Biometric authentication has become popular in modern society. It takes less time and effort for users when compared to conventional password authentication. Furthermore, biometric authentication was considered more secure than password authentication because it was more difficult to steal biometric information when compared to passwords. However, given the development of high-spec cameras and image recognition technology, the risk of the theft of biometric information, such as fingerprints, is increasing. Additionally, biometric authentication exhibits lower and less stable accuracy than that of password authentication. To solve the aforementioned issues, we propose two-factor authentication combining password-input and biometric authentication of the hand. We adopt Leap Motion to measure physical and behavioral features related to hands. Subsequently, a random forest classifier determines whether the hand features belongs to a genuine user. Our authentication system architecture completes the biometric authentication by using a limited amount of data obtained within a few seconds when a user enters a password. The advantage of the proposed method is that it prevents intrusion by biometric authentication even if a password is stolen. Our experimental results for 21 testers exhibit 94.98% authentication accuracy in a limited duration, 2.52 s on an average while inputting a password.
机译:生物特征认证已经在现代社会中流行。与传统的密码验证相比,它为用户节省了时间和精力。此外,生物特征认证被认为比密码认证更安全,因为与密码相比,窃取生物特征信息更加困难。但是,随着高规格相机和图像识别技术的发展,诸如指纹之类的生物信息被盗的风险正在增加。另外,生物特征认证比密码认证具有更低和更不稳定的准确性。为了解决上述问题,我们提出了结合密码输入和手的生物特征认证的两因素认证。我们采用Leap Motion来测量与手相关的身体和行为特征。随后,随机森林分类器确定手形特征是否属于真实用户。我们的身份验证系统体系结构通过使用用户输入密码后几秒钟内获得的有限数量的数据来完成生物特征认证。所提出的方法的优点在于,即使密码被盗,它也可以防止通过生物特征认证的入侵。我们针对21位测试人员的实验结果在有限的时间内显示了94.98%的认证准确度,平均输入密码时为2.52 s。

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