INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT International Peer Reviewed & Refereed Journals, Open Access Journal ISSN Approved Journal No: 2456-4184 | Impact factor: 8.76 | ESTD Year: 2016
Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.76 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI)
The substantial and automated access to Web resources through robots has made it essential for Web service providers to make some anticipation about whether "user" is a human or a robot. A Human Interaction Proof (HIP) like Completely Automated Public Turing test to tell Computers and Humans Apart (CAPTCHA) offers a way to make such a distinction. Captcha is a reverse Turing test used by Web service providers to secure human interaction assumed services from Web bots. Several Web services that include but are not limited to free e-mail accounts, submission of e-mail, online polls, chat rooms, search engines, blogs, password systems, etc. use Captcha as a defensive mechanism against automated Web bots. This paper presents a deep dive survey on various aspects of Captcha methods that include its types, generation methods, robustness against attacks and various usability aspects. It presents a review of existing Captcha schemes besides relative merits of text and image based on them. We propose a new image-based Captcha technique known as Style Area Captcha (SACaptcha) that is based on the neural style transfer technique. To pass the test, users are required to click foreground style-transferred regions in an image based on a brief description.
Keywords:
recognition; text-based CAPTCHA; convolutional neural network; deep learning
Cite Article:
"SURVEY ON DEEP LEARNING TECHNIQUES IN BREAKING TEXT", International Journal of Novel Research and Development (www.ijnrd.org), ISSN:2456-4184, Vol.8, Issue 11, page no.a34-a37, November-2023, Available :http://www.ijnrd.org/papers/IJNRD2311003.pdf
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ISSN:
2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar| ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.76 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
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