首页 | 本学科首页   官方微博 | 高级检索  
     


Synthetic handwritten CAPTCHAs
Authors:Achint Oommen Thomas  Amalia Rusu  Venu Govindaraju[Author vitae]
Affiliation:CUBS, CEDAR, State University of New York at Buffalo, 201 Bell Hall, Amherst, NY 14280, USA
Abstract:CAPTCHAs (completely automated public Turing test to tell computers and humans apart) are in common use today as a method for performing automated human verification online. The most popular type of CAPTCHA is the text recognition variety. However, many of the existing printed text CAPTCHAs have been broken by web-bots and are hence vulnerable to attack. We present an approach to use human-like handwriting for designing CAPTCHAs. A synthetic handwriting generation method is presented, where the generated textlines need to be as close as possible to human handwriting without being writer-specific. Such handwritten CAPTCHAs exploit the differential in handwriting reading proficiency between humans and machines. Test results show that when the generated textlines are further obfuscated with a set of deformations, machine recognition rates decrease considerably, compared to prior work, while human recognition rates remain the same.
Keywords:HIP  CAPTCHA  Handwriting generation
本文献已被 ScienceDirect 等数据库收录!
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号