Captcha

CAPTCHA

A CAPTCHA (Completely Automated Public Turing test to tell Computers and Humans Apart) is a type of challenge-response test used in computing to determine whether the user is human. The term was coined in 2003 by Luis von Ahn, Manuel Blum, Nicholas J. Hopper, and John Langford.

Purpose

CAPTCHAs are primarily used to prevent automated software from performing actions that degrade the quality of service of a given system. For example, they are used to prevent bots from spamming web forms, creating fake accounts, or scraping data from websites.

Types of CAPTCHA

Text-based CAPTCHA

The most common type of CAPTCHA involves the user being presented with a distorted image of text and being asked to type the text into a box. This relies on the difficulty that computers have in recognizing distorted text, a task that is relatively easy for humans.

Image-based CAPTCHA

Image-based CAPTCHAs require users to select images that meet a certain criterion, such as "select all images with traffic lights." This type of CAPTCHA leverages the human ability to recognize objects in images, which is still a challenging task for computers.

Audio CAPTCHA

Audio CAPTCHAs are used to ensure accessibility for visually impaired users. They present a series of spoken numbers or letters that the user must type in. These are designed to be difficult for automated systems to interpret.

reCAPTCHA

reCAPTCHA is a free CAPTCHA service offered by Google. It uses advanced risk analysis techniques to differentiate between humans and bots. reCAPTCHA often requires users to identify objects in images or simply check a box labeled "I'm not a robot."

Challenges and Criticisms

CAPTCHAs have been criticized for being difficult for humans to solve, especially for those with disabilities. They can also be bypassed by sophisticated bots or by using machine learning techniques. Additionally, CAPTCHAs can be a source of frustration for users, leading to a poor user experience.

Future of CAPTCHA

The future of CAPTCHA involves developing more user-friendly and secure methods of distinguishing humans from bots. This includes using behavioral analysis, such as tracking mouse movements or keystroke dynamics, and leveraging artificial intelligence to create more adaptive and less intrusive tests.

Also see

• Turing test
• Botnet
• Web security
• Machine learning