Application of Decision Trees in the Identification of Fraudulent Websites

1
Christian Layme Fernández
Christian Layme Fernández
2
José Manuel Suri Canaza
José Manuel Suri Canaza
3
David Jose Peña Ugarte
David Jose Peña Ugarte
4
Jhon Yoset Luna Quispe
Jhon Yoset Luna Quispe

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Computer security is a very important area in any system that has an internet connection, because there are fraudulent websites that can carry out criminal actions towards a person, organization or other entity. Therefore, it is necessary to be able to detect which websites are fraudulent before being able to enter it, for this an implementation was developed through Decision Trees with the Python language to detect and classify them as Legitimate, Suspicious and Fraudulent through 1353 cases that they rank websites.

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Funding

No external funding was declared for this work.

Conflict of Interest

The authors declare no conflict of interest.

Ethical Approval

No ethics committee approval was required for this article type.

Data Availability

Not applicable for this article.

Christian Layme Fernández. 2026. \u201cApplication of Decision Trees in the Identification of Fraudulent Websites\u201d. Global Journal of Computer Science and Technology - H: Information & Technology GJCST-H Volume 22 (GJCST Volume 22 Issue H1): .

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High-quality research on decision trees for identifying fraudulent websites and enhancing cybersecurity.
Journal Specifications

Crossref Journal DOI 10.17406/gjcst

Print ISSN 0975-4350

e-ISSN 0975-4172

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GJCST-H Classification: DDC Code: 621.38928 LCC Code: TH9737
Version of record

v1.2

Issue date

July 19, 2022

Language

English

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Application of Decision Trees in the Identification of Fraudulent Websites

Christian Layme Fernández
Christian Layme Fernández
José Manuel Suri Canaza
José Manuel Suri Canaza
David Jose Peña Ugarte
David Jose Peña Ugarte
Jhon Yoset Luna Quispe
Jhon Yoset Luna Quispe

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