Enhancing the Security of Large Character Set CAPTCHAs Using Transferable Adversarial Examples

Summary

Researchers propose ACG (Adversarial Large Character Set CAPTCHA Generation), a framework for defending large character set CAPTCHAs against automated attacks. It pairs a Fine-grained Generation Module with an Ensemble Generation Module that adds global perturbations, and they release Adv-Eval, a toolkit with datasets from 10 popular Chinese CAPTCHA schemes. Experiments show the average success rate of diverse attacks falls from 51.52% to 2.56%.

Topics

• Adversarial machine learning

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