Application of Decision Trees in the Identification of Fraudulent Websites

Authors

  • Christian Layme Fernndez

  • Jos Manuel Suri Canaza

  • David Jose Pea Ugarte

  • Jhon Yoset Luna Quispe

Keywords:

rboles de decisin, crisp-dm, minera de datos, clasificacin, sitios web

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.

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How to Cite

Christian Layme Fernndez, Jos Manuel Suri Canaza, David Jose Pea Ugarte, & Jhon Yoset Luna Quispe. (2022). Application of Decision Trees in the Identification of Fraudulent Websites. Global Journal of Computer Science and Technology, 22(H1), 7–11. Retrieved from https://computerresearch.org/index.php/computer/article/view/101452

Application of Decision Trees in the Identification of Fraudulent Websites

Published

2022-07-19