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A Novel Construction of Correlation-Based Image CAPTCHA with Random Walk

  • Qian-qian Wu
  • Jian-jun Lang
  • Song-jie Wei
  • Mi-lin Ren
  • Erik Seidel
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 670)

Abstract

CAPTCHA has been widely adopted throughout the World Wide Web to achieve network security by preventing malicious interruption or abuse of server resources. Existing text-based and image-based CAPTCHA techniques are not robust enough to resist sophisticated attacks using pattern recognition and machine learning. To overcome this challenge, we designed a new approach to construct an image-based CAPTCHA by using a random walk on image with correlated contents, which capitalizes on human knowledge on the relevance of images. The usability and robustness of the proposed scheme have been evaluated by both numerical analysis and empirical evidence. Early testing has shown it to be a promising approach to enhancing and replacing the existing Web CAPTCHA techniques when fighting against bots.

Keywords

CAPTCHA Image correlation Random walk 

Notes

Acknowledgements

This material is based upon work supported by the China NSF grant No. 61472189, the CERNET Innovation Project No. NGII20160601, and the Innovation Projects of Beijing Engineering Research Center of Next Generation Internet and Applications.

The authors confirm that an ethic approval for this particular type of study is not required in accordance with the policy of the involved institutes.

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Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  • Qian-qian Wu
    • 1
  • Jian-jun Lang
    • 2
  • Song-jie Wei
    • 1
  • Mi-lin Ren
    • 3
  • Erik Seidel
    • 1
  1. 1.CSE SchoolNanjing University of Science and TechnologyNanjingChina
  2. 2.Affiliated High SchoolNanjing Normal UniversityNanjingChina
  3. 3.Beijing Engineering Research Center of NGI & Its Major Application Technologies Co. Ltd.BeijingChina

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