Thai CAPTCHA : Construction and Analysis
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Abstract
- Currently, there are many websites that allow users to upload information to their servers such as member registration forms, webboard and etc. These websites are targeted by bots to create bogus information, i.e. sales or fake member registration, manipulated by bot-master. By surveying, we found that bots attacking on several websites always come from places outside Thailand. We therefore propose the new technique to construct CAPTCHA by using Thai characters to distinguish users that know Thai language from bot-machines. In addition, simple mathematic functions and background noise are inserted to enhance efficiency. We also analyze the results from Thai OCR which is named Arnthai to define properties of proposed Thai CAPTCHA more efficiently.
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References
2. http://members.cox.net/randar/botfaq.html 3. Von Ahn L, Blum M, and Langford J, The Captcha Project.http://www.captcha.net
4. Carlos Javier Hernandez-Castro, Arturo Ribagorda,” Pitfalls in CAPTCHA design and implementation: The Math CAPTCHA, a case study “, computers & security journal 2 0 1 0 ,Pages 141- 157
5. http://www.google.com/recaptcha
6. Mori G, Malik J (2003), “Recognizing Objects in Adversarial Clutter: Breaking a VisualCAPTCHA,” Proc. of the Computer Vision and Pattern Recognition (CVPR) Conference, IEEE Computer Society, vol.1, pages:I-134 - I-141, June 18-20, 2003
7. Kumar Chellapilla and Patrice Y. Simard. Using Machine Learning to Break Human Interaction Proofs (HIPs). In NIPS. เกษรินทร์ ชาวเกวียน และ วรพล ลีลาเกียรติสกุล : การสร้างและการวิเคราะห์ Thai CAPTCHA
8. M. Hassan Shirali-Shahreza, Mohammad Shirali-Shahreza, “Localized CAPTCHA for Illiterate People”, International Conference on Intelligent and Advanced Systems 2007,Pages 675-679
9. MSN Audio CAPTCHA, https://signup.live.com/
10. Recaptcha Audio CAPTCHA, http://recaptcha.net/learnmore.html
11. http://www.nectec.or.th/img/index.php?option=com_content&task=view&id=25&Itemid=39&lang=enม OCR ที่ชื่อว่า Arnthai เพื่อที่จะกำหนดคุณสมบัติของ CAPTCHA ที่นำเสนอให้มีประสิทธิภาพมากขึ้น