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Completely Automated Public Turing test to tell Computers and Humans Apart,short for CAPTCHA, is an essential and relatively easy way to defend againstmalicious attacks implemented by bots. The security and usability trade-offlimits the use of massive geometric transformations to interfere deep modelrecognition and deep models even outperformed humans in complex CAPTCHAs. Thediscovery of adversarial examples provides an ideal solution to the securityand usability trade-off by integrating adversarial examples and CAPTCHAs togenerate adversarial CAPTCHAs that can fool the deep models. In this paper, weextend the definition of adversarial CAPTCHAs and propose a classificationmethod for adversarial CAPTCHAs. Then we systematically review some commonlyused methods to generate adversarial examples and methods that are successfullyused to generate adversarial CAPTCHAs. Also, we analyze some defense methodsthat can be used to defend adversarial CAPTCHAs, indicating potential threatsto adversarial CAPTCHAs. Finally, we discuss some possible future researchdirections for adversarial CAPTCHAs at the end of this paper.

A Survey of Adversarial CAPTCHAs on its History, Classification and Generation