[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.
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.
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.
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.
| CAPTCHA Type | Accuracy | | --- | --- | | Simple text-based CAPTCHA | 90% | | Distorted text-based CAPTCHA | 80% | | Noisy text-based CAPTCHA | 70% |
[1] L. von Ahn, M. Blum, N. J. Hopper, and J. Langford, "CAPTCHA: Using Hard AI Problems for Security," in Proceedings of the 22nd Annual International Cryptology Conference, 2000.
[3] Y. LeCun, Y. Bengio, and G. Hinton, "Deep Learning," Nature, vol. 521, no. 7553, pp. 436-444, 2015.
[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.
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. captcha+breaker
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. Sahu, "A Survey on CAPTCHA and CAPTCHA Breaking
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. [3] Y. LeCun
| CAPTCHA Type | Accuracy | | --- | --- | | Simple text-based CAPTCHA | 90% | | Distorted text-based CAPTCHA | 80% | | Noisy text-based CAPTCHA | 70% |
[1] L. von Ahn, M. Blum, N. J. Hopper, and J. Langford, "CAPTCHA: Using Hard AI Problems for Security," in Proceedings of the 22nd Annual International Cryptology Conference, 2000.
[3] Y. LeCun, Y. Bengio, and G. Hinton, "Deep Learning," Nature, vol. 521, no. 7553, pp. 436-444, 2015.