• DocumentCode
    3337790
  • Title

    CAPTCHA design based on moving object recognition problem

  • Author

    Cui, JingSong ; Wang, LiJing ; Mei, JingTing ; Zhang, Da ; Wang, Xia ; Peng, Yang ; Zhang, WuZhou

  • Author_Institution
    Sch. of Comput., Wuhan Univ., Wuhan, China
  • fYear
    2010
  • fDate
    23-25 June 2010
  • Firstpage
    158
  • Lastpage
    162
  • Abstract
    CAPTCHA is a test that can tell humans and computer programs apart automatically. The aim is to allow the server to identify the visitor is a human or a computer, and only provide services to human. It can improve the current server system and user information security. The static plane visual CAPTCHA based on OCR problems with the advantages of implementation and operation[1] become the mainstream of the current CAPTCHA technology application form. However, with a variety of targeted text segmentation technologies merging, such CAPTCHA based on OCR problems is faced with increasing security threats. In this paper, a new CAPTCHA based on the moving object identification and tracking problems is proposed, which is referred to biological motion vision model. An Innovative Single-frame Zero-knowledge rule is also put forward to make the CAPTCHA generation algorithm based on Edge Mutation. An attacker can log on the test service system, only after he solves the moving object recognition problem. Such animation CAPTCHA will be able to resist the attacks of all the static OCR technology, and resist the mainstream of attacks against the moving object detection.
  • Keywords
    Application software; Automatic testing; Face detection; Humans; Information security; Merging; Object recognition; Optical character recognition software; Resists; Target tracking; CAPTCHA; Edge Mutation; Moving Object Recognition; Network Security; Single-frame Zero-knowledge;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Sciences and Interaction Sciences (ICIS), 2010 3rd International Conference on
  • Conference_Location
    Chengdu, China
  • Print_ISBN
    978-1-4244-7384-7
  • Electronic_ISBN
    978-1-4244-7386-1
  • Type

    conf

  • DOI
    10.1109/ICICIS.2010.5534730
  • Filename
    5534730