Machine learning Ensemble Methods for Detection of Phishing in Website

In this research article, we propose to use a learning method with combinations such as the competitive random forest algorithm and the cloud gradient boosting and algorithm to efficiently and accurately identify customers who follow phishing websites. Phishing is one of the biggest cybercrimes in today's digital world. The attackers attempt to Obtain victims’ credentials, account information, and other sensitive information by impersonating existing and generally trusted individuals or organizations are visible and similar to phishing websites. On real websites. Online commerce has also grown to increase the number of phishing scams. Network Security is the most difficult task to achieve, and development. Automated systems are in place for phishing website detection. Need machine learning is one of the best solutions for this situation because it can provide the correct classification system as well as check the status of phishing strategies.

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Publication Details

Journal
Global Journal of Engineering Innovations and Interdisciplinary Research
Published
2025-06-27
DOI
https://doi.org/10.33425/3066-1226.1133
Primary Topic
Spam and Phishing Detection
Type
article
Field-Weighted Citation Impact
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article

Machine learning Ensemble Methods for Detection of Phishing in Website

A R Jayakrishnan, Nisha Pradeepa S.P., Yamini Ch, J. G. et al.
Global Journal of Engineering Innovations and Interdisciplinary Research
Spam and Phishing Detection
article

Machine learning Ensemble Methods for Detection of Phishing in Website

A R Jayakrishnan, Nisha Pradeepa S.P., Yamini Ch, J. G., Chandana Sri Vadlamudi
article en

Abstract

In this research article, we propose to use a learning method with combinations such as the competitive random forest algorithm and the cloud gradient boosting and algorithm to efficiently and accurately identify customers who follow phishing websites. Phishing is one of the biggest cybercrimes in today's digital world. The attackers attempt to Obtain victims’ credentials, account information, and other sensitive information by impersonating existing and generally trusted individuals or organizations are visible and similar to phishing websites. On real websites. Online commerce has also grown to increase the number of phishing scams. Network Security is the most difficult task to achieve, and development. Automated systems are in place for phishing website detection. Need machine learning is one of the best solutions for this situation because it can provide the correct classification system as well as check the status of phishing strategies.

Global Journal of Engineering Innovations and Interdisciplinary ResearchVol. 5(4)
Vignan's Foundation for Science, Technology & Research (IN), Vignana Jyothi Institute of Management (IN)
Openalex Percentile: Top 73%
Spam and Phishing Detection
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Machine learning Ensemble Methods for Detection of Phishing in Website — A R Jayakrishnan, Nisha Pradeepa S.P., et al. · Global Journal of Engineering Innovations and Interdisciplinary Research (2025) | TGRS Research Map | TGRS