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Stream/Area:
-
Subject:
-
Paper ID:
10.55041/IJSREM16419
Volume:
6 |
9 |
Sep 2022
Pages:
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
CAPTCHAs (Completely Automated Public Turing test to tell Computers and Humans Apart) are distortions of texts or images so that they are still recognizable to most humans but can become difficult for a computer to recognize. Additionally, many CAPTCHAs also inject noise or additional structures such as blobs or lines into the image to further make it difficult to recognize. They are primarily employed as security measures on websites to prevent bots from accessing or performing transactions on the site. On the other hand, machine learning (ML) algorithms, in particular deep learning (DL) neural networks have been trained with significant success on similar problems such as handwritten digit recognition. This motivates us to build an ML-based CAPTCHA breaker that maps CAPTCHAs to their solutions.
KEYWORDS
Publication Date
9/21/2022
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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Conflict of Interest
The authors declare no conflict of interest related to this research work.
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