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Book ChapterDOI

An Overview of Various Types of CAPTCHA

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TLDR
An analysis of the different categories of CAPTCHAs, the attacks against them and ideas and designs to develop more robust and user-friendly CAPTCHA in the coming future are presented in this paper.
Abstract
Authentication is a commonly used technique in software applications to ensure whether the correct user is getting access to secured services or not. Due to the fast pace of data growth, there is an increasing need for security of online data. This is commonly achieved by the use of various CAPTCHAs. CAPTCHAs are an implementation of reverse Turing test. Turing test is used to distinguish between humans and computers. A fundamental property that the use of CAPTCHA necessitates is that the CAPTCHA must be easy and efficient for humans but difficult for computers. CAPTCHAs are used to protect the data from malicious bots and web crawlers. They are not only used in web sites but also used in banking transactions, cloud computing, distributed infrastructures and income tax services. In this paper, an analysis of the different categories of CAPTCHAs, the attacks against them and ideas and designs to develop more robust and user-friendly CAPTCHAs in the coming future are presented.

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References
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Journal ArticleDOI

reCAPTCHA: Human-Based Character Recognition via Web Security Measures

TL;DR: This research explored whether human effort can be channeled into a useful purpose: helping to digitize old printed material by asking users to decipher scanned words from books that computerized optical character recognition failed to recognize.
Journal ArticleDOI

Telling humans and computers apart automatically

TL;DR: In this paper, lazy cryptographers do AI and show how lazy they can be, and how they do it well, and why they do so poorly, and they are lazy.
Proceedings Article

Asirra: a CAPTCHA that exploits interest-aligned manual image categorization.

TL;DR: A CAPTCHA that asks users to identify cats out of a set of 12 photographs of both cats and dogs, and two novel algorithms for amplifying the skill gap between humans and computers that can be used on many existing CAPTCHAs are described.
Proceedings ArticleDOI

BaffleText: a Human Interactive Proof

TL;DR: BaffleText is proposed, a CAPTCHA which uses non-English pronounceable words to defend against dictionary attacks, and Gestalt-motivated image-masking degradations to defending against image restoration attacks, which confirms the human legibility and user acceptance of BaffleText images.
Journal ArticleDOI

Pessimal print: a reverse Turing test

TL;DR: This work proposes a variant of the Turing test using pessimal print: that is, low-quality images of machine-printed text synthesized pseudo-randomly over certain ranges of words, typefaces, and image degradations and shows experimentally that judicious choice of these ranges can ensure that the images are legible to human readers but illegible to several of the best present-day optical character recognition (OCR) machines.
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