Title :
CAPTCHA Security: A Case Study
Author :
Yan, Jeff ; El Ahmad, Ahmad Salah
Author_Institution :
Newcastle Univ., Newcastle upon Tyne, UK
Abstract :
A simple but novel attack can break some CAPTCHAs with a success rate higher than 90 percent. In contrast to early work that relied on sophisticated computer vision or machine learning techniques, the authors used simple pattern recognition algorithms to exploit fatal design errors.
Keywords :
pattern recognition; security of data; CAPTCHA security; computer vision; fatal design error; machine learning techniques; pattern recognition algorithm; Computer vision; Humans; Image converters; Optical character recognition software; Pattern recognition; Pixel; Security; Shearing; Text analysis; Web services; CAPTCHA; dictionary attacks; pixel count; security;
Journal_Title :
Security & Privacy, IEEE
DOI :
10.1109/MSP.2009.84
