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Sketcha: A Captcha Based on Line Drawings of 3D Models

机译:Sketcha:基于3D模型线条图的验证码

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This paper introduces a captcha based on upright orientation of line drawings rendered from 3D models. The models are selected from a large database, and images are rendered from random viewpoints, affording many different drawings from a single 3D model. The captcha presents the user with a set of images, and the user must choose an upright orientation for each image. This task generally requires understanding of the semantic content of the image, which is believed to be difficult for automatic algorithms. We describe a process called covert filtering whereby the image database can be continually refreshed with drawings that are known to have a high success rate for humans, by inserting randomly into the captcha new images to be evaluated. Our analysis shows that covert filtering can ensure that captchas are likely to be solvable by humans while deterring attackers who wish to learn a portion of the database. We performed several user studies that evaluate how effectively people can solve the captcha. Comparing these results to an attack based on machine learning, we find that humans possess a substantial performance advantage over computers.
机译:本文介绍了一种基于3D模型绘制的线条图的垂直方向的验证码。从大型数据库中选择模型,然后从随机视点渲染图像,从而从单个3D模型提供许多不同的图形。验证码为用户提供了一组图像,用户必须为每个图像选择一个垂直方向。该任务通常需要理解图像的语义内容,这被认为对于自动算法是困难的。我们描述了一种称为隐式过滤的过程,该过程可通过将随机插入验证码的新图像中进行评估,从而用已知对人类有较高成功率的图纸不断刷新图像数据库。我们的分析表明,秘密过滤可以确保验证码很容易被人类解决,同时阻止希望学习数据库一部分的攻击者。我们进行了几项用户研究,评估了人们如何有效地解决验证码。将这些结果与基于机器学习的攻击进行比较,我们发现人类拥有比计算机更大的性能优势。

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