Captcha+breaker Exclusive File

[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

The term CAPTCHA was first introduced in 2000 by Luis von Ahn, Manuel Blum, Nicholas J. Hopper, and John Langford [1]. The primary motivation behind CAPTCHA was to create a challenge-response test that could distinguish humans from computers. The test was designed to be easy for humans to solve but difficult for computers to pass. CAPTCHAs have been widely adopted in various applications, including online registration, voting systems, and online transactions. Sahu, "A Survey on CAPTCHA and CAPTCHA Breaking

CAPTCHAs are widely used to prevent automated programs from accessing a system or performing certain actions. However, with the advancement of artificial intelligence and machine learning techniques, CAPTCHAs have become increasingly vulnerable to being broken. This paper provides a comprehensive overview of CAPTCHA, its history, types, and vulnerabilities. Additionally, we discussed various CAPTCHA breaker techniques, including machine learning-based approaches, and analyzed their effectiveness. The experimental 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. such as deep learning

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.