1. 563.10.3 CAPTCHA Presented by: Sari Louis SPAM Group: Marc Gagnon, Sari Louis, Steve White University of Illinois Spring 2006

2. 2 Agenda Definition Background Applications Types of CAPTCHAs Breaking CAPTCHAs Proposed Approach Conclusion

3. 3 Definition CAPTCHA stands for Completely Automated Public Turing test to tell Computers and Humans Apart A.K.A. Reverse Turing Test, Human Interaction Proof The challenge: develop a software program that can create and grade challenges most humans can pass but computers cannot

4. 4 Background First used by Altavista in1997 –Reduced SPAM add-url by over 95% CMU/Yahoo! –Automated the creating and grading of challenges PARC –Relies on document image degradation to prevent successful OCR –Conducted user-focused studies to assess the effectiveness of CAPTCHAs

5. 5 Background CAPTCHAs are based on open AI problems Breaking CAPTCHAs help advance AI by solving these open problems Improving CAPTCHAs help telling computers and human apart Win-win situation

6. 6 Background - Papers Pessimal Print: A Reverse Turing Test Allison L. Coates, Henry S. Baird, Richard J. Fateman Telling Humans and Computer Apart Automatically Luis von Ahn, Manuel Blum, and John Langford CAPTCHA: Using Hard AI Problems for Security Luis von Ahn, Manuel Blum, Nicholas J. Hopper, and John Langford Using Machine Learning to Break Visual Human Interaction Proofs (HIPs) Kumar Chellapilla, Patrice Y. Simard

7. 7 Applications Free email services Online polls Dictionary attacks Newsgroups, Blogs, etc… SPAM

8. 8 Types of CAPTCHAs Text based –Gimpy, ez-gimpy –Gimpy-r, Google CAPTCHA –Simard’s HIP (MSN) Graphic based –Bongo –Pix Audio based

9. 9 Text Based CAPTCHAs Gimpy, ez-gimpy –Pick a word or words from a small dictionary –Distort them and add noise and background Gimpy-r, Google’s CAPTCHA –Pick random letters –Distort them, add noise and background Simard’s HIP –Pick random letters and numbers –Distort them and add arcs

10. 10 Text Based CAPTCHAs

11. 11 Graphic Based CAPTCHAs Bongo –Display two series of blocks –User must find the characteristic that sets the two series apart –User is asked to determine which series each of four single blocks belongs to Difference? thick vs. thin lines

12. 12 Graphic Based CAPTCHAs PIX –Create a large database of labeled images –Pick a concrete object –Pick four images of the object from the images database –Distort the images –Ask the user to pick the object for a list of words

13. 13 Graphic Based CAPTCHAs Dog Pool

14. 14 Audio Based CAPTCHAs Pick a word or a sequence of numbers at random Render them into an audio clip using a TTS software Distort the audio clip Ask the user to identify and type the word or numbers

15. 15 Breaking CAPTCHAs Most text based CAPTCHAs have been broken by software –OCR –Segmentation Other CAPTCHAs were broken by streaming the tests for unsuspecting users to solve.

16. 16 Proposed Approach Very similar to PIX Pick a concrete object Get 6 images at random from images.google.com that match the object Distort the images Build a list of 100 words: 90 from a full dictionary, 10 from the objects dictionary Prompt the user to pick the object from the list of words

17. 17 Proposed Approach - Technical Make an HTTP call to images.google.com and search for the object Screen scrape the result of 2-3 pages to get the list of images Pick 6 images at random Randomly distort both the images and their URLs before displaying them Expire the CAPTCHA in 30-45 seconds

18. 18 Proposed Approach - Benefits The database already exists and is public The database is constantly being updated and maintained Adding “concrete objects” to the dictionary is virtually instantaneous Distortion prevents caching hacks Quick expiration limits streaming hacks

19. 19 Proposed Approach - Drawbacks Not accessible to people with disabilities (which is the case of most CAPTCHAs) Relies on Google’s infrastructure Unlike CAPTCHAs using random letters and numbers, the number of challenge words is limited