International Journal of Contents

  • 제5권3호
  • /
  • Pages.50-56
  • /
  • 2009
  • /
  • 1738-6764(pISSN)
  • /
  • 2093-7504(eISSN)
한국콘텐츠학회 (The Korea Contents Association)
권호 표지
DOI QR코드

DOI QR Code

A Korean CAPTCHA Study: Defeating OCRs In a New CAPTCHA Context By Using Korean Syllables

  • 발행 : 2009.09.28
PDF 다운로드
⟨ 이전 논문 다음 논문 ⟩

초록

Internet is being used for several activities by a great range of users. These activities include communication, e-commerce, education, and entertainment. Users are required to register regarding website in order to enroll web activities. However, registration can be done by automated hacking software. That software make false enrollments which occupy the resources of the website by reducing the performance and efficiency of servers, even stop the entire web service. It is crucial for the websites to have a system which has the capability of differing human users and computer programs in reading images of text. Completely Automated Public Turing Test to Tell Computers and Human Apart (CAPTCHA) is such a defense system against Optical Character Recognition (OCR) software. OCR can be defined as software which work for defeating CAPTCHA images and make countless number of registrations on the websites. This study proposes a new CAPTCHA context that is Korean CAPTCHA by means of the method which is splitting CAPTCHA images into several parts with random rotation values, and drawing random lines on a grid background by using Korean characters only. Lines are in the same color with the CAPTCHA text and they provide a distortion of image with grid background. Experimental results show that Korean CAPTCHA is a more secure and effective CAPTCHA type for Korean users rather than current CAPTCHA types due to the structure of Korean letters and the algorithm we are using: rotation and splitting. In this paper, the algorithm of our method is introduced in detail.

키워드

참고문헌

  1. Blum, M., 2000, The CAPCTHA Project, Completely Automatic Public Turing Test to Tell Computers and Humans Apart", Dept. of Computer Science, Carnegie-Mellon University, http://www.captcha.net.
  2. Athanasopoulos, E., Antonatos, S., "Enchanced CAPTCHAs: Using Animation to Tell Humans and Computers Apart", LNCS, 4237, 2006, pp. 97-108.
  3. Wang, S., Baird, H., Bentley, J., "CAPTCHA Challenge Tradeoffs: Familarity of Strings versus Degradation of Images", the 18th International Conference on Pattern Recognition, ICPR'06, IEEE, 2006. https://doi.org/10.1109/ICPR.2006.355
  4. Von Ahn, L., Blum, M., Nicholas, J.H., Langford, J., "CAPTCHA: Using Hard AI Problems for Security", In Proceedings of Eurocrypt, 2003, pp.294-311.
  5. Shahreza, M., Shahreza, S., "Preventing Mobile Software Cracking Software", IEEE, Innovations in Information Technology, Dubai, 2006, pp. 1-5. https://doi.org/10.1109/INNOVATIONS.2006.301936
  6. Moy, G., Jones, N., Harkless, C., Potter, R., "Distortion estimation technique in solving visual CAPTCHAs", Proc. of the 2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2004, vol.2, 2004, pp.23-28. https://doi.org/10.1109/CVPR.2004.1315140
  7. G. Mori, and J. Malik, "Recognizing Objects in Adversarial Clutter: Breaking a Visual CAPTCHA", Proc. of IEEE CS Society Conf. on Computer Vision and Pattern Recognition, Madison, 2003, pp. 134-141. https://doi.org/10.1109/CVPR.2003.1211347
  8. Coates, A.L., Baird, H.S, Fateman, R.J., "PessimalPrint: A Reverse Turing Test", Proc.of 6th Int. Conf. on Document Analysis and Recognition, Seattle, WA, USA, 2001, pp.1154 - 1158.
  9. Yahoo! mail, http://mail.yahoo.com [06/10/2008]
  10. Microsoft Hotmail, http://www.hotmail.com [06/10/2008]
  11. Google Gmail, http://mail.google.com [06/10/2008]
  12. Chew M. and Baird H. S., "BaffleText: a Human Interactive Proof", Proc of 10th SPIE/IS&T Document Recognition and Retrieval Conf. (DRR2003), Santa Clara, CA, 2003, pp. 305-316.
  13. Chan, T.Y., 2003, "Using a Text-to-Speech Synthesizer to Generate a Reverse Turing Test", Proceedings of the 15th IEEE International Conference on Tools with Artificial Intelligence, pp. 226 - 232. https://doi.org/10.1109/TAI.2003.1250195
  14. Ince, I.F., Yengin, I., Salman, Y.B., Cho, H.G., Yang, T.C. "Designing CAPTCHA Algorithm: Splitting and Rotating the Images against OCRs", International Conference on Convergence and Hybrid Information Technology, ICCIT 08, IEEE, 2008. https://doi.org/10.1109/ICCIT.2008.195