Browse > Article
http://dx.doi.org/10.3745/KIPSTC.2010.17C.1.027

Reliable Image-Text Fusion CAPTCHA to Improve User-Friendliness and Efficiency  

Moon, Kwang-Ho (인하대학교 정보공학과)
Kim, Yoo-Sung (인하대학교 정보통신공학부)
Abstract
In Web registration pages and online polling applications, CAPTCHA(Completely Automated Public Turing Test To Tell Computers and Human Apart) is used for distinguishing human users from automated programs. Text-based CAPTCHAs have been widely used in many popular Web sites in which distorted text is used. However, because the advanced optical character recognition techniques can recognize the distorted texts, the reliability becomes low. Image-based CAPTCHAs have been proposed to improve the reliability of the text-based CAPTCHAs. However, these systems also are known as having some drawbacks. First, some image-based CAPTCHA systems with small number of image files in their image dictionary is not so reliable since attacker can recognize images by repeated executions of machine learning programs. Second, users may feel uncomfortable since they have to try CAPTCHA tests repeatedly when they fail to input a correct keyword. Third, some image-base CAPTCHAs require high communication cost since they should send several image files for one CAPTCHA. To solve these problems of image-based CAPTCHA, this paper proposes a new CAPTCHA based on both image and text. In this system, an image and keywords are integrated into one CAPTCHA image to give user a hint for the answer keyword. The proposed CAPTCHA can help users to input easily the answer keyword with the hint in the fused image. Also, the proposed system can reduce the communication costs since it uses only a fused image file for one CAPTCHA. To improve the reliability of the image-text fusion CAPTCHA, we also propose a dynamic building method of large image dictionary from gathering huge amount of images from theinternet with filtering phase for preserving the correctness of CAPTCHA images. In this paper, we proved that the proposed image-text fusion CAPTCHA provides users more convenience and high reliability than the image-based CAPTCHA through experiments.
Keywords
Image-Text Fusion CAPTCHA; Filtering; Text Matching; Content-Base Matching;
Citations & Related Records
Times Cited By KSCI : 1  (Citation Analysis)
연도 인용수 순위
1 Greg Mori, Jitendra Malik, "Recognizing Objects in Adversarial Clutter: Breaking a Visual CAPTCHA," Proceedings of IEEE Computer Vision and Pattern Recognition, Vol.1, pp.134-141, June, 2003.
2 Jeff Yan, Ahmad Salah EI Ahmad, "Breaking Visual CAPTCHAs with Naïve Pattern Recognition Algorithms," Proceedings of Annual Computer Security Applications Conference, pp.279-291, 2007.
3 Kumar Chellapilla, Patrice Y. Simard, "Using Machine Learning to Break Visual Human Interaction Proofs(HIPs)," MIT Press, Advances in Neural Information Processing Systems 17, pp.265-272, 2004.
4 Microsoft (Live Mail 서비스), Google(Gmail 서비스)의 CAPTCHA Image, http://www.tzywen.com/photos/misc/captcha.PNG.
5 Naver Developer Center, http://dev.naver.com/openapi/apis/contents/image.
6 Luis von Ahn, Manuel Blum, Nicholas J. Hopper, John Langford, "CAPTCHA: Using Hard AI Problems for Security," EUROCRYPT, pp.294-311, May, 4-8 2003.
7 Kurt Alfred Kluever, "Breaking the PayPal HIP: A Comparison of Classifiers," MS Thesis,Department of Computer Science, Rochester Institute of Technology, May 2008.
8 Philippe Golle, "Machine Learning Attacks against the Asirra CAPTCHA," Proceedings of Conference on Computer and Communications Security, pp.535-542, October, 2008.
9 Monica Chew, J. D. Tygar, "Image Recognition CAPTCHAs," Proceedings of International Information Security Conference, pp.268-279, September, 2004.
10 강전일, 맹영재, 김군순, 양대헌, 이경희, "복수의 이미지를 합성하여 사용하는 이미지 기반의 캡차와 이를 위한 안전한 운용 방법", 정보보호학회논문지, 제18권 제 4호, pp.153-166, 2008.   과학기술학회마을
11 Prasad, Sumeet, "Google's CAPTCHA busted in recent spammer tactics", Websense Blog, February, 22 2008.
12 The Official CAPTCHA Site, http://www.captcha.net/, 2009.
13 Wikipedia, ""CAPTCHA"", http://en.wikipedia.org/wiki/Captcha, 2009.
14 Luis von Ahn, Manuel Blum, John Langford, ""Telling humans and computers apart automatically"", Communications of ACM, Vol.47, No.2, pp.57-60, February, 2004.   DOI   ScienceOn
15 Gregg Keizer, "Spammers' bot cracks Microsoft's CAPTCHA: Bot beats Windows Live Mail's registration test 30% to 35% of the time, says Websense", Computerworld, February, 7 2008.
16 Jeff Yan, Ahmad Salah El Ahmad, "A Low-cost Attack on a Microsoft CAPTCHA," a research paper, School of Computing Science, Newcastle University, UK, December, 21 2008.
17 Jeremy Elson, John R. Douceur, Jon Howell, "Asirra: A CAPTCHA that Exploits Interest-Aligned Manual Image Categorization," Proceedings of Conference on Computer and Communications Security, pp.535-542, October, 2007.
18 Carnegie Mellon University, "ESP-PIX CAPTCHA Application," http://server251.theory.cs.cmu.edu/cgi-bin/esp -pix/esp-pix.
19 THEPCSpy, "KittenAuth," http://www.thepcspy.com.