Applying Machine Learning for Identifying Fraud Sites
Abstract & Details
Research Area
Computer science
Keywords
To publishing the paper
Abstract
Offenders looking for
sensitive information create illicit clones
of legitimate websites and e-mail
accounts. The email will contain actual
company logos and phrases. When a
user clicks on one of these hackers'
links, the hackers obtain access to all of
the user's sensitive information,
including bank account information,
personal login passwords, and
photos.Random Forest and Decision
Tree algorithms are widely used in
current systems, and their accuracy
must be improved. The current models
have a low latency. Existing systems
lack a specialised user interface.
License
This work is licensed under a Creative
Commons
Attribution-ShareAlike 4.0 International License.
Author Information
| # | Name | Institute / Affiliation |
|---|---|---|
| 1 | Renuka Reddy | AMC Engineering of College |
How to Cite
Use the following formats to cite this article in your research.
APA Style
Reddy, Renuka (2023). Applying Machine Learning for Identifying Fraud Sites. International Journal of Advance Research and Innovative Ideas In Education, 9(4), 834-837.
MLA Style
Reddy, Renuka. "Applying Machine Learning for Identifying Fraud Sites." International Journal of Advance Research and Innovative Ideas In Education, vol. 9, no. 4, 2023, pp. 834-837.
IEEE Style
Renuka Reddy, "Applying Machine Learning for Identifying Fraud Sites," International Journal of Advance Research and Innovative Ideas In Education, vol. 9, no. 4, pp. 834-837, 2023.
Vancouver Style
Reddy Renuka. Applying Machine Learning for Identifying Fraud Sites. International Journal of Advance Research and Innovative Ideas In Education. 2023;9(4):834-837.
Harvard Style
Reddy, Renuka (2023) 'Applying Machine Learning for Identifying Fraud Sites', International Journal of Advance Research and Innovative Ideas In Education, 9(4), pp. 834-837.
Chicago Style
Reddy, Renuka. "Applying Machine Learning for Identifying Fraud Sites." International Journal of Advance Research and Innovative Ideas In Education 9, no. 4 (2023): 834-837.
Turabian Style
Reddy, Renuka. "Applying Machine Learning for Identifying Fraud Sites." International Journal of Advance Research and Innovative Ideas In Education 9, no. 4 (2023): 834-837.
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