| Title | DeCaptcha: Cracking captcha using Deep Learning Techniques |
| Publication Type | Conference Paper |
| Year of Publication | 2021 |
| Authors | Mistry, Rahul, Thatte, Girish, Waghela, Amisha, Srinivasan, Gayatri, Mali, Swati |
| Conference Name | 2021 5th International Conference on Information Systems and Computer Networks (ISCON) |
| Keywords | Analytical models, bidirectional LSTM, CAPTCHA, captchas, CNN, composability, computer networks, Computers, Deep Learning, GANs, Human Behavior, pubcrawl, RNN, security, usability |
| Abstract | CAPTCHA or Completely Automated Public Turing test to Tell Computers and Humans Apart is a technique to distinguish between humans and computers by generating and evaluating tests that can be passed by humans but not computer bots. However, captchas are not foolproof, and they can be bypassed which raises security concerns. Hence, sites over the internet remain open to such vulnerabilities. This research paper identifies the vulnerabilities found in some of the commonly used captcha schemes by cracking them using Deep Learning techniques. It also aims to provide solutions to safeguard against these vulnerabilities and provides recommendations for the generation of secure captchas. |
| DOI | 10.1109/ISCON52037.2021.9702512 |
| Citation Key | mistry_decaptcha_2021 |
DeCaptcha: Cracking captcha using Deep Learning Techniques