Knowing Captchas Using Deep Learning

laasya kashimalla; Pranitha A; T SoumyaSree

International Journal of Embedded Systems and Emerging Technologies

Knowing Captchas Using Deep Learning

Abstract

Websites can use CAPTCHA (Completely Automated Public Turing Test to Differentiate Computers from Humans) to distinguish between humans and machines and prevent automated attacks by programmers and malicious programmers. Studies on CAPTCHA recognition have the potential to uncover security flaws, advance CAPTCHA technology, and even advance handwriting and license plate recognition. However, the whole objective of the CAPTCHAs can be bypassed by utilizing the principles of deep learning and computer vision. Convolutional neural networks (CNN) enable the automatic passing of this test. A CNN is a deep learning algorithm that uses an image as input before giving distinct features in the image a value that further aids in differentiating one feature from another. Its major objective is without losing features that are crucial for obtaining an optimized forecast, to convert the photos into a form that is much easier to handle. Future work on this project will involve expanding the CAPTCHA recognition algorithm to handle noisier, bigger and CAPTCHAs with all conceivable symbols.

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Knowing Captchas Using Deep Learning

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