PowerPoint Presentation On Captcha

PPT On Captcha

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Captcha Presentation Transcript:

1. Intro
CAPTCHA Completely Automated Public Turing test to tell Computers and Humans Apart Invented at CMU by Luis von Ahn, Manuel Blum, et. al A program that is a challenge – response test to separate humans from computer programs

2. Generic CAPTCHAs
distort letters and numbers Distorted characters are presented to user User has to recognize the distorted letters If the guessed letters are correct, the user is inferred to be a human and allowed access Else, user is a bot and denied access

3. Humans can read the distorted and noisy text Current OCRs cannot read them

4. Background
Why CAPTCHA was needed? Sabotage of online polls Spam emails Abusing free online accounts Tampering with rankings on recommendation systems (like EBay, Amazon)

5. Altavista first used a crude CAPTCHA in their sites Resulted in 95% spam reduction Yahoo partnered CMU to counter these threats in Messenger chat service. Luis von Ahn and Manuel Blum of CMU trademarked CAPTCHA in 2000

6. What is a Turing test?
Proposed by Alan Turing To test a machine’s level of intelligence Human judge asks questions to two participants, one is a machine, he doesn’t know which is which If judge can’t tell which is the machine, the machine passes the test CAPTCHA employs a reverse Turing test, judge = CAPTCHA program, participant = user if user passes CAPTCHA, he is human if user fails, it is a machine

7. Types of CAPTCHAs
Text based: Simple, normal language questions: What is sum of three and thirty-five? If today is Saturday, what is day after tomorrow? Which of mango, table, water is a fruit? Very effective, needs a large question bank Cognitively challenged users find it hard

8. Gimpy:
Designed by Yahoo and CMU Picks up 10 random words from dictionary and distorts, fills with noise User has to recognize at least 3 words If user is correct, he is admitted

9. EZ-Gimpy:
A modified version of Gimpy Yahoo used this version in Messenger Has only 1 random string of characters Not a dictionary word, so not prone to dictionary attack Not a good implementation, already broken by OCRs

10. For more please refer our PPT. Thanks.