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CAPTCHA challenge strings: problems and improvements

机译：验证码挑战字符串：问题和改进

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摘要

A CAPTCHA is a Completely Automated Public Test to tell Computers and Humans Apart. Typical CAPTCHAs present a challenge string consisting of a visually distorted sequence of letters and perhaps numbers, which in theory only a human can read. Attackers of CAPTCHAs have two primary points of leverage: Optical Character Recognition (OCR) can identify some characters, while nonuniform probabilities make other characters relatively easy to guess. This paper uses a mathematical theory of assurance to characterize the probability that a correct answer to a CAPTCHA is not just a lucky guess. We examine the three most common types of challenge strings, dictionary words, Markov text, and random strings, and find substantial weaknesses in each. We therefore propose improvements to Markov text, and new challenges based on the consonant-vowel-consonant (CVC) trigrams of psychology. Theory and experiment together quantify problems in current challenges and the improvements offered by modifications.
机译：验证码是一种完全自动化的公共测试，用于区分计算机和人类。典型的验证码会显示挑战字符串，该字符串由视觉上变形的字母序列（也许是数字）组成，理论上只有人类可以阅读。 CAPTCHA的攻击者有两个主要的利用点：光学字符识别（OCR）可以识别某些字符，而不一致的概率使其他字符相对容易猜测。本文使用保证的数学理论来描述对验证码的正确答案不仅仅是幸运的猜测的概率。我们研究了挑战字符串，字典词，马尔可夫文本和随机字符串这三种最常见的类型，并发现了每种类型中的实质性弱点。因此，我们建议对马尔可夫文本进行改进，并基于心理学的辅音-元音-辅音（CVC）语法，提出新的挑战。理论和实验共同量化了当前挑战和改进带来的改进中的问题。

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