Original scientific paper

https://doi.org/10.31803/tg-20230219213151

Design of Efficient Phishing Detection Model using Machine Learning

Bong-Hyun Kim ; School of Software, Major of Computer Engineering, Seowon University, 377-3 Musimseo-ro, Seowon-gu, Cheongju-si, Chungcheongbuk-do, 28674, Republic of Korea *

* Corresponding author.

Abstract

Recently, there have been cases of phishing attempts to steal personal information through fake sites disguised as major sites. Although phishing attacks continue and increase, countermeasures remain in the form of defense after identifying the attack. Therefore, in this paper, we designed a phishing detection model using machine learning that provides knowledge and prediction by learning patterns from data input to a computer. For this, an analysis model was built using sklearn logistic regression, and the phishing probability was visualized using a heatmap. In addition, a graph was used to visually indicate the result, and a function for attribute information of a phishing website was provided.

Keywords

ensemble method; heatmap; machine learning; phishing detection; random forest; sklearn

Hrčak ID:

313793

URI

https://hrcak.srce.hr/313793

Publication date:

15.2.2024.

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