This is a code release of IJCNN 2023 oral long paper Fighting Attacks on Large Character Set CAPTCHAs Using Transferable Adversarial Examples.
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Adversarial CAPTCHAs Generation Part
can generate adversarial CAPTCHAs.-
generate_AE_on_character.py
can useM_VNI_CT_FGSM
to generate adversarial examples in the characters of the CAPTCHA. -
generate_AE_on_background.py
can useSVRE_MI_FGSM
to generate adversarial examples in the background of the CAPTCHA. -
config.py
contains the parameter setting and path setting of the adversarial CAPTCHAs generation process. -
To generate adversarial CAPTCHAs, you can run
generate_AE_on_character.py
first and then rungenerate_AE_on_background.py
.
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Dataset and Model Preparation Part
contains the synthetic dataset and models.-
Model_Library_Building
contains the architecture and training parameters for all character detection and recognition models. -
Dataset_Generation
contains scripts to generate the synthetic dataset.
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For security and rights considerations, we do not open source the real CAPTCHA dataset and trained attack models. If you need them for research purposes, please contact yfu2668@gmail.com.