A Completely Automated Public Turing test to tell Computer and Humans Apart (CAPTCHA) is a variation of the Turing test, in which a challenge is used to distinguish humans from computers (‘bots’) on the internet. They are commonly used to prevent the abuse of online services; for example, malicious users have written automated programs that signup for thousands of free email accounts and send S...

reCaptcha is a very popular CAPTCHA system on the Internet. Due to its design, we find that reCaptcha figures have certain feature that can potentially weaken this system. This paper discussed the design of reCaptcha, and use some simple Machine Learning algorithm to find a way to tell the difference between “control word” and “unknown word”. We also designed the experiment to evaluate our hypo...

Based on the notion of “emergence”, Xu et al. (Usenix Security 2012; TDSC 2013) developed the first concrete instantiation of emerging-image moving-object (EIMO) CAPTCHAs using 2D hollow objects (codewords), shown to be usable and believed to be secure. In this paper, we highlight the hidden security weaknesses of such a 2D EIMO CAPTCHA design. A key vulnerability is that the camera projection ...

Recent document image understanding R&D intended to protect Internet services against abuse by programs is summarized. The accelerating pace of introduction of working CAPTCHAs — completely automatic public Turing tests to tell computers and humans apart — is reported, and the ability of these CAPTCHAs to resist attack is critiqued. Attacks on PARC’s ‘BaffleText’ CAPTCHA by the DIA, CV, and sec...

In this paper, we have proposed a system to grade CAPTCHA strength, according to various parameters determined by breaking the CAPTCHA. There are basically four major steps involved in the system.First step is preprocessing which includes – binarization and noise removal.Second step is segmenting the image into individual characters. Third step is to obtain skeletons of characters i.e., Thinnin...

This study focuses on a machine learning approach to the CAPTCHA recognition problem that requires minimal preprocessing of inputs. Both the feed-forward neural nets and the self-organizing maps used in this study took the raw image pixels as input with only simple segmentation and translation performed in advance. The models were trained and tested on four and five letter CAPTCHAs using either...

CAPTCHAs is an interesting of research are short for Completely Automated Public Turing test to tell Computers and Humans Apart. The purpose of a CAPTCHA is to block form submissions from spam bots –automated scripts that harvest email addresses from publicly available web forms. We introduce a new CAPTCHA which is based on identifying the color of image, object or background. This actually req...

We present a new method for image taxonomy. Our formulation shows how the combination of automated metadata-based analysis and knowledge-acquisition tools can help build better image search applications. We build on top of existing metadata-based techniques to image taxonomy and combine them to human assistance, in order to guarantee some minimal level of semantic soundness. Knowledge from huma...

As a result of continuing advances in computer capabilities, it is becoming increasingly difficult to distinguish between humans and computers in the digital world. We propose using the fundamental human ability to distinguish between things that are aesthetically pleasing and those that are not as the basis of a method to verify that a communicating party is human. We discuss one possible impl...

Spam over internet telephony (SPIT) refers to all unsolicited and massive scale attempts to establish voice communication with oblivious users of voice over internet protocol (VoIP) services. SPIT exhibits a significant increase over the last years, thus developing into a serious threat with adverse impact and costs for the business economy. An audio completely automated public Turing test to t...