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Development of Personal Identification Number Authorization Algorithm Using Real- Time Eye Tracking Dynamic Keypad Generation

机译:使用实时眼跟踪和动态键盘生成个人识别码授权算法的开发

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The digital financial transaction is on a continuous rise and going to be the order of the day. These transactions rely on the entry of the Personal Identification Number (PIN) by the user. The PIN is a common user authentication method for many applications such as ATM's, unlocking personal devices. Cyber-crimes are committed by shoulder surfing or thermal tracking. PIN entry is found vulnerable to password attacks such as shoulder surfing or thermal tracking. Intruders try to gain passwords or personal identification numbers (PIN) by glancing over the user's shoulder and observing the pattern of PIN entry (shoulder surfing). Thermal tracking is another method followed by cyber thieves, using the heat traces to decode the entered PIN by the user. This paper proposes a novel approach to authorization of PIN. To demonstrate the same, a web application is developed with trio-based authentications using machine learning techniques. Initially, the application detects and recognizes the user's face. A dynamic keypad is displayed which prompts the user to provide input PIN via eye blink. User's eye is detected and monitored by the application in order to capture the PIN and verifies the same with the existing PIN in the database. On a successful PIN verification process, the application allows the user to proceed with the transaction. The results show the proposed novel approach is better than existing approaches.
机译:数字金融交易是连续上升,将是当天的顺序。这些交易依赖于用户输入个人识别码(PIN)的条目。 PIN是许多应用程序的常用用户认证方法,例如ATM,解锁个人设备。网络犯罪是由肩部冲浪或热跟踪犯下的。 PIN条目易受密码攻击(如肩部冲浪或热跟踪)。入侵者试图通过浏览用户的肩膀并观察PIN进入(肩部冲浪)的模式来获得密码或个人识别号码(PIN)。热跟踪是另一种方法,然后是网络盗贼,使用热迹来解码输入的引脚。本文提出了一种新的PIN授权方法。为了证明相同的是,使用机器学习技术使用基于Trio的身份验证开发了Web应用程序。最初,应用程序检测并识别用户的脸部。显示动态键盘,其提示用户通过眨眼提供输入引脚。通过应用程序检测和监视用户的眼睛,以便捕获引脚并将其与数据库中的现有引脚相同。在成功的PIN验证过程中,应用程序允许用户继续交易。结果表明,拟议的新方法比现有方法更好。

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