Denial-of-Service (DoS) flooding attacks have become a serious threat to the reliability of the Internet. Web servers face all kinds of users; some of them engage malicious activities to degrade or completely block network services, such as flooding attacks. As a result, lots of resource and bandwidth on web sites might be wasted. While many approaches exist to filter network-level attacks, the...

The ability to tell humans and computers apart is imperative to protect many services from misuse and abuse. For this purpose, tests called CAPTCHAs or HIPs have been designed and put into production. Recent history shows that most (if not all) can be broken given enough time and commercial interest: CAPTCHA design seems to be a much more difficult problem than previously thought. The assumptio...

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...

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...