Captcha+breaker May 2026

[4] J. K. Lal, P. S. Kumar, and S. K. Sahu, "A Survey on CAPTCHA and CAPTCHA Breaking Techniques," Journal of Intelligent Information Systems, vol. 54, no. 2, pp. 267-286, 2020.

We conducted experiments on a dataset of text-based CAPTCHAs to evaluate the effectiveness of the machine learning-based approach. The results are shown in Table 1. captcha+breaker

| CAPTCHA Type | Accuracy | | --- | --- | | Simple text-based CAPTCHA | 90% | | Distorted text-based CAPTCHA | 80% | | Noisy text-based CAPTCHA | 70% | Sahu, "A Survey on CAPTCHA and CAPTCHA Breaking

Future work includes exploring more advanced machine learning-based approaches, such as deep learning, to improve the accuracy of CAPTCHA breakers. Additionally, we plan to investigate the use of CAPTCHAs in various applications, such as online registration and voting systems, and evaluate their effectiveness in preventing automated programs from accessing these systems. "Foundations of Statistical Natural Language Processing

The results show that the machine learning-based approach can achieve high accuracy on simple text-based CAPTCHAs, but the accuracy decreases as the CAPTCHA becomes more distorted or noisy.

[2] C. D. Manning and H. Schütze, "Foundations of Statistical Natural Language Processing," MIT Press, 1999.