Application of Decision Trees in the Identification of Fraudulent Websites

α
Christian Layme Fernández
Christian Layme Fernández
σ
José Manuel Suri Canaza
José Manuel Suri Canaza
ρ
David Jose Peña Ugarte
David Jose Peña Ugarte
Ѡ
Jhon Yoset Luna Quispe
Jhon Yoset Luna Quispe

Send Message

To: Author

Application of Decision Trees in the Identification of Fraudulent Websites

Article Fingerprint

ReserarchID

CSTITEU1V2

Application of Decision Trees in the Identification of Fraudulent Websites Banner

AI TAKEAWAY

Connecting with the Eternal Ground
  • English
  • Afrikaans
  • Albanian
  • Amharic
  • Arabic
  • Armenian
  • Azerbaijani
  • Basque
  • Belarusian
  • Bengali
  • Bosnian
  • Bulgarian
  • Catalan
  • Cebuano
  • Chichewa
  • Chinese (Simplified)
  • Chinese (Traditional)
  • Corsican
  • Croatian
  • Czech
  • Danish
  • Dutch
  • Esperanto
  • Estonian
  • Filipino
  • Finnish
  • French
  • Frisian
  • Galician
  • Georgian
  • German
  • Greek
  • Gujarati
  • Haitian Creole
  • Hausa
  • Hawaiian
  • Hebrew
  • Hindi
  • Hmong
  • Hungarian
  • Icelandic
  • Igbo
  • Indonesian
  • Irish
  • Italian
  • Japanese
  • Javanese
  • Kannada
  • Kazakh
  • Khmer
  • Korean
  • Kurdish (Kurmanji)
  • Kyrgyz
  • Lao
  • Latin
  • Latvian
  • Lithuanian
  • Luxembourgish
  • Macedonian
  • Malagasy
  • Malay
  • Malayalam
  • Maltese
  • Maori
  • Marathi
  • Mongolian
  • Myanmar (Burmese)
  • Nepali
  • Norwegian
  • Pashto
  • Persian
  • Polish
  • Portuguese
  • Punjabi
  • Romanian
  • Russian
  • Samoan
  • Scots Gaelic
  • Serbian
  • Sesotho
  • Shona
  • Sindhi
  • Sinhala
  • Slovak
  • Slovenian
  • Somali
  • Spanish
  • Sundanese
  • Swahili
  • Swedish
  • Tajik
  • Tamil
  • Telugu
  • Thai
  • Turkish
  • Ukrainian
  • Urdu
  • Uzbek
  • Vietnamese
  • Welsh
  • Xhosa
  • Yiddish
  • Yoruba
  • Zulu

Abstract

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.

References

8 Cites in Article
  1. Mary Tinti (2020). Colab.
  2. Sisca Octarina,Fitri Puspita,Evi Yuliza,Indrawati Indrawati (2020). PENDAMPINGAN PENGGUNAAN GOOGLE COLAB PADA PEMBELAJARAN PYTHON DAN MACHINE LEARNING BAGI DOSEN MATEMATIKA DI PALEMBANG.
  3. (2020). Pandas Basics -Learn Python -Free Interactive Python Tutorial.
  4. (2020). NumPy.
  5. S Programacion En Castellano (2020). Introducción a la librería Matplotlib de Python.
  6. David Paper (2020). Scikit-Learn Regression Tuning.
  7. Fabian Pedregosa,; Gaël Varoquaux,Alexandre Gramfort,Vincent Michel,; Bertrand Thirion,; Olivier,Grisel; Mathieu Blondel,Peter Prettenhofer,Ron Weiss,Vincent Dubourg,Jake Vanderplas,Alexandre Passos,David Cournapeau,Matthieu Perrot,Édouard Duchesnay (2011). Scikit-learn: Machine Learning in Python.
  8. J Gallardo (2007). Metodología para el Desarrollo de Proyectos en Minería de Datos CRISP-DM" oldemarrodriguez.

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.

How to Cite 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): .

Download Citation

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

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

v1.2

Issue date

July 19, 2022

Language
es
Experiance in AR

Explore published articles in an immersive Augmented Reality environment. Our platform converts research papers into interactive 3D books, allowing readers to view and interact with content using AR and VR compatible devices.

Read in 3D

Your published article is automatically converted into a realistic 3D book. Flip through pages and read research papers in a more engaging and interactive format.

Article Matrices
Total Views: 2824
Total Downloads: 45
2026 Trends
Related Research

Published Article

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.

Our website is actively being updated, and changes may occur frequently. Please clear your browser cache if needed. For feedback or error reporting, please email [email protected]

Request Access

Please fill out the form below to request access to this research paper. Your request will be reviewed by the editorial or author team.
X

Quote and Order Details

Contact Person

Invoice Address

Notes or Comments

This is the heading

Lorem ipsum dolor sit amet, consectetur adipiscing elit. Ut elit tellus, luctus nec ullamcorper mattis, pulvinar dapibus leo.

High-quality academic research articles on global topics and journals.

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

Research Journals