Robust image-based CAPTCHA generation using adversarial attack
Yuqian Wen · Third International Conference on Intelligent Computing and Human-Computer Interaction (ICHCI 2022) · 2023
CAPTCHA (Completely Automated Public Truing test to tell Computers and Humans Apart) is a technology used to protect network security, distinguishing humans and machines by tests that humans can easily pass but machines fail. However, with the wide application of CAPTCHAs, many cracking methods have emerged. Specifically, Deep Learning (DL) have played an important role in in destroying CAPTCHA, which brings a great threat to the security of CAPTCHAs. Therefore, it is of great significance to improve the security of the CAPTCHAs against cracking methods based on deep learning technology. This paper focuses on image-based CAPTCHAs which is the most widely used type, and proposes an image-based CAPTCHA generation method based on adversarial examples. Starting from the actual application scenario of CAPTCHA, we improve it on the basis of I-FGSM (Iterative Fast Gradient Sign Method) by randomly transforming the input samples and performing secondary processing to adversarial noise. Experiments show that our method can effectively improve the robustness and transferability of the CAPTCHA.