Image-Based CAPTCHA Recognition Using Deep Learning Models
Authors: 
Huthaifa Mohammed Kanoosh, Ammar Farooq Abbas, Noora Nazar Kamal, Zainab Mejeed Khadim, Duaa A. Majeed, Sameer AlgburiAuthors Info & Claims
Huthaifa Mohammed Kanoosh, Ammar Farooq Abbas, Noora Nazar Kamal, Zainab Mejeed Khadim, Duaa A. Majeed, Sameer AlgburiAuthors Info & ClaimsPages 273 - 278
Abstract
This study dives into the efficacy of deep learning models within the field of CAPTCHA recognition, with a primary focus on bolstering online security measures. Our inquiry suggests a unique perspective by using Convolutional Neural Networks (CNNs) to recognize and categorize CAPTCHA images appropriately. The procedural methodology comprises preprocessing these images and training CNN models to partition them into discrete groups. Through thorough experimentation and assessment, our proposed methodology exposes promising outcomes, as notably shown by our CNN Model 4 obtaining an amazing accuracy rate of 96%. These results demonstrate the usefulness of deep learning algorithms in the field of CAPTCHA detection. while stressing their crucial function in decreasing cybersecurity concerns. This study adds greatly to the development of CAPTCHA recognition systems. highlighting the criticality of deploying deep learning models to enhance internet security procedures.
CCS CONCEPTS • Machine learning • Artificial intelligence • Visualization
Additional Keywords and Phrases: Deep learning, CAPTCHA recognition, Convolutional Neural Networks (CNN), Image.
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https://datasetninja.com/google-recaptcha-image
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Published In
May 2024
367 pages
ISBN:9798400716928
DOI:10.1145/3660853
Copyright © 2024 ACM.
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Published: 23 June 2024
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AICCONF '24
AICCONF '24: Cognitive Models and Artificial Intelligence Conference
May 25 - 26, 2024
İstanbul, Turkiye
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