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IllusionPIN: Shoulder-Surfing Resistant Authentication Using Hybrid Images

机译:IllusionPIN:使用混合图像的抗肩膀冲浪身份验证

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摘要

We address the problem of shoulder-surfing attacks on authentication schemes by proposing IllusionPIN (IPIN), a PIN-based authentication method that operates on touchscreen devices. IPIN uses the technique of hybrid images to blend two keypads with different digit orderings in such a way, that the user who is close to the device is seeing one keypad to enter her PIN, while the attacker who is looking at the device from a bigger distance is seeing only the other keypad. The user's keypad is shuffled in every authentication attempt, since the attacker may memorize the spatial arrangement of the pressed digits. To reason about the security of IPIN, we developed an algorithm which is based on human visual perception and estimates the minimum distance from which an observer is unable to interpret the keypad of the user. We tested our estimations with 84 simulated shoulder-surfing attacks from 21 different people. None of the attacks was successful against our estimations. In addition, we estimated the minimum distance from which a camera is unable to capture the visual information from the keypad of the user. Based on our analysis, it seems practically almost impossible for a surveillance camera to capture the PIN of a smartphone user when IPIN is in use.
机译:通过提出IllusionPIN(IPIN)(一种在触摸屏设备上运行的基于PIN的身份验证方法),我们解决了对身份验证方案进行网上冲浪攻击的问题。 IPIN使用混合图像技术将两种具有不同数字顺序的小键盘混合在一起,从而使靠近设备的用户看到一个小键盘输入她的PIN,而攻击者则从更大的角度查看设备距离只能看到另一个键盘。用户的键盘在每次身份验证尝试中都会打乱,因为攻击者可能会记住所按数字的空间布置。为了说明IPIN的安全性,我们开发了一种基于人类视觉的算法,该算法可以估算观察者无法解释用户键盘的最小距离。我们用来自21个不同人的84次模拟肩膀冲浪攻击测试了我们的估计。根据我们的估计,没有一次攻击成功。此外,我们估算了相机无法从用户键盘捕获视觉信息的最小距离。根据我们的分析,当使用IPIN时,监视摄像机几乎几乎不可能捕获智能手机用户的PIN。

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  • 作者单位

    Department of Computer Science and Engineering, New York University Tandon School of Engineering, Brooklyn, NY, USA;

    Department of Computer Science and Engineering, New York University Tandon School of Engineering, Brooklyn, NY, USA;

    Department of Computer Science and Engineering, New York University Tandon School of Engineering, Brooklyn, NY, USA;

    Department of Computer Science and Engineering, New York University Tandon School of Engineering, Brooklyn, NY, USA;

  • 收录信息
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Authentication; Pins; Visualization; Observers; Usability; Cameras;

    机译:身份验证;引脚;可视化;观察者;可用性;相机;
  • 入库时间 2022-08-17 13:05:58

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