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International Journal for Research Trends and Innovation
International Peer Reviewed & Refereed Journals, Open Access Journal
ISSN Approved Journal No: 2456-3315 | Impact factor: 8.14 | ESTD Year: 2016
Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.14 (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)
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Impact Factor : 8.14
Issue per Year : 12
Volume Published : 11
Issue Published : 118
Article Submitted : 21470
Article Published : 8508
Total Authors : 22383
Total Reviewer : 805
Total Countries : 157
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| Paper Title: | Detection of URL frauds using Machine Learning Algorithms. |
| Authors Name: | B.Naga Raju , G.ROHITH , N.Mounika , N.Suresh , P.Naga Indu Sri |
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IJRTI_189725
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| Published Paper Id: | IJRTI2404137 |
| Published In: | Volume 9 Issue 4, April-2024 |
| DOI: | |
| Abstract: | Technology in our current era has become very important, as it has facilitated many services for us and has become faster and easier than before, as we can complete many things simultaneously and as quickly as possible. Phishing websites have proven to be a major security concern. Phishing is still one of the best and most successful ways for hackers to steal sensitive information. We used the different classification algorithm, by analyzing data and classifying fake and legitimate sites to reduce the problem of phishing in different services. Here, we are implemented the two different ML algorithms such as random forest and logistic regression. One of the main challenge is ensuring that the algorithms are able to detect new and evolving types of phishing attacks. This project is used to predict the legitimate websites and phishing websites. The experimental results shows that some performance metrics such as accuracy, precision, recall and f1 score. |
| Keywords: | Machine Learning models, Random Forest, Logistic Regression, URL features extraction. |
| Cite Article: | "Detection of URL frauds using Machine Learning Algorithms.", International Journal for Research Trends and Innovation (www.ijrti.org), ISSN:2455-2631, Vol.9, Issue 4, page no.1015 - 1021, April-2024, Available :http://www.ijrti.org/papers/IJRTI2404137.pdf |
| Downloads: | 000205230 |
| ISSN: |
2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016 An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 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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Published Paper ID: IJRTI2404137
Registration ID:189725
Published In: Volume 9 Issue 4, April-2024
DOI (Digital Object Identifier):
Page No: 1015 - 1021 Country: Vijayawada, Andhra Pradesh, India Research Area: Information Technology Publisher : IJ Publication Published Paper URL : https://www.ijrti.org/viewpaperforall?paper=IJRTI2404137 Published Paper PDF: https://www.ijrti.org/papers/IJRTI2404137 |
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ISSN: 2456-3315
Impact Factor: 8.14 and ISSN APPROVED,
Journal Starting Year (ESTD) : 2016
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