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BioTouchPass: Handwritten Passwords for Touchscreen Biometrics

机译:Biotouchpass:触摸屏生物识别的手写密码

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This work enhances traditional authentication systems based on Personal Identification Numbers (PIN) and One-Time Passwords (OTP) through the incorporation of biometric information as a second level of user authentication. In our proposed approach, users draw each digit of the password on the touchscreen of the device instead of typing them as usual. A complete analysis of our proposed biometric system is carried out regarding the discriminative power of each handwritten digit and the robustness when increasing the length of the password and the number of enrolment samples. The new e-BioDigit database, which comprises on-line handwritten digits from 0 to 9, has been acquired using the finger as input on a mobile device. This database is used in the experiments reported in this work and it is available together with benchmark results in GitHub.(1) 1. https://github.com/BiDAlab/eBioDigitDB. Finally, we discuss specific details for the deployment of our proposed approach on current PIN and OTP systems, achieving results with Equal Error Rates (EERs) ca. 4.0 percent when the attacker knows the password. These results encourage the deployment of our proposed approach in comparison to traditional PIN and OTP systems where the attack would have 100 percent success rate under the same impostor scenario.
机译:这项工作通过将生物识别信息作为第二级用户身份验证,基于个人识别号码(PIN)和一次性密码(OTP)来增强传统认证系统。在我们提出的方法中,用户在设备的触摸屏上绘制密码的每个数字,而不是像往常一样键入它们。对我们所提出的生物识别系统的完全分析是关于当增加密码长度和注册样本的数量时每个手写数字和鲁棒性的辨别力。新的E-BioDIGIT数据库包括从0到9的在线手写数字,使用手指作为移动设备上的输入获取。该数据库用于本工作中报告的实验中,它可以与GitHub中的基准结果一起使用。(1)1。https://github.com/bidalab/ebiodigitdb。最后,我们讨论了在当前PIN和OTP系统上部署我们提出的方法的具体细节,实现了相同的错误率(EERS)CA的结果。攻击者知道密码时的4.0%。这些结果鼓励与传统的PIN和OTP系统相比部署我们的攻击在同一冒号情景下的攻击率为100%的成功率。

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