DETECTING PHISHING WEBSITES WITH AN ENSEMBLE MACHINE LEARNING METHOD

phishing websites now pose a critical threat to digital infrastructure across industries.They frequently serve as the initial vector for various cyber intrusions that steal, change, or gain access to both customer and company data.This study presents a new way to find phishing websites by combining attribute selection and data point derivation methods with an ensemble-based machine learning algorithm.It does this after looking at all the research that is already out there.The proposed method uses a carefully chosen dataset to build and test ensemble models that can accurately predict phishing activity. I.

Publication Details

Journal
IARJSET
Published
2025-06-30
DOI
https://doi.org/10.17148/iarjset.2025.12702
Primary Topic
Spam and Phishing Detection
Type
article
Field-Weighted Citation Impact
0.00
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article

DETECTING PHISHING WEBSITES WITH AN ENSEMBLE MACHINE LEARNING METHOD

IARJSET
Spam and Phishing Detection
article

DETECTING PHISHING WEBSITES WITH AN ENSEMBLE MACHINE LEARNING METHOD

article en

Abstract

phishing websites now pose a critical threat to digital infrastructure across industries.They frequently serve as the initial vector for various cyber intrusions that steal, change, or gain access to both customer and company data.This study presents a new way to find phishing websites by combining attribute selection and data point derivation methods with an ensemble-based machine learning algorithm.It does this after looking at all the research that is already out there.The proposed method uses a carefully chosen dataset to build and test ensemble models that can accurately predict phishing activity. I.

IARJSETVol. 12(7)
Openalex Percentile: Top 78%
Spam and Phishing Detection
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DETECTING PHISHING WEBSITES WITH AN ENSEMBLE MACHINE LEARNING METHOD · IARJSET (2025) | TGRS Research Map | TGRS