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. 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% 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% success rate under the same impostor scenario.
翻译:这项工作加强了基于个人身份号码和一次性密码的传统认证系统,将生物鉴别信息作为第二层次的用户认证,从而增强了基于个人身份号码(PIN)和一次性密码(OTP)的传统认证系统。在我们提议的方法中,用户在设备触摸屏上抽取密码的每一个数字,而不是像往常一样打字。对我们提议的生物鉴别系统进行了全面分析,涉及每个手写数字的歧视性力量,以及在增加密码长度和注册样本数量时的稳健性。新的e-BioDigit数据库由0至9的在线手写数字组成,已经用手指作为移动设备的投入而获得。在这项工作中报告的实验中使用了这个数据库,该数据库与GitHub的基准结果一起提供。最后,我们讨论了在目前的PIN和OTP系统部署我们拟议的方法的具体细节,在攻击者知道密码时,以等差率取得4.0%的结果鼓励采用我们提议的办法来比较传统的PIN和OTP系统,因为根据同样的假设,攻击将达到100%的成功率。