Advanced Phishing Detection System: Integrating Deep Learning Machine Learning and Transformers for Real-Time Protection

P. Phanindra Kumar Reddy, S. Fahimuddin, D. Hameed, D. Allipeera, V. Rajkumar, P. Harshavardhan

2025

Abstract

This research article proposes an Advanced Phishing Detection System that integrates advanced feature extraction, exploratory data analysis (EDA), and various machine learning models to enable real-time detection of phishing threats. Online data is being processed to extract key features and then extensive EDA is being done to identify patterns from which phishing activity can be deduced. We perform the detection of phishing websites using techniques like Decision Tree, Random Forest, Multilayers perceptrons (MLP), XGBoost, Autoencoder Neural Network, Support Vector Machines (SVM) - 6 well known AI models. In the experimental results, it was observed that Multilayer perceptron was right behind XGBoost with training accuracy of 0.858 and testing accuracy of 0.863 against maximum accuracy of XGBoost where it achieved training accuracy of 0.866 and testing accuracy of 0.864. Though least accurate, Autoencoder Neural Network and SVM give their corresponding results as complement, whereas Random forest and decision tree models outperforms them all. Using Flask, an easy-to-use interface is developed so that a real-world application can be easily done, to get instant insight and feedback regarding a potential phishing site.

Paper Citation

in Harvard Style

Reddy P., Fahimuddin S., Hameed D., Allipeera D., Rajkumar V. and Harshavardhan P. (2025). Advanced Phishing Detection System: Integrating Deep Learning Machine Learning and Transformers for Real-Time Protection. In Proceedings of the 1st International Conference on Research and Development in Information, Communication, and Computing Technologies - ICRDICCT`25; ISBN 978-989-758-777-1, SciTePress, pages 5-10. DOI: 10.5220/0013875800004919

in Bibtex Style

@conference{icrdicct`2525,
author={P. Reddy and S. Fahimuddin and D. Hameed and D. Allipeera and V. Rajkumar and P. Harshavardhan},
title={Advanced Phishing Detection System: Integrating Deep Learning Machine Learning and Transformers for Real-Time Protection},
booktitle={Proceedings of the 1st International Conference on Research and Development in Information, Communication, and Computing Technologies - ICRDICCT`25},
year={2025},
pages={5-10},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013875800004919},
isbn={978-989-758-777-1},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 1st International Conference on Research and Development in Information, Communication, and Computing Technologies - ICRDICCT`25
TI - Advanced Phishing Detection System: Integrating Deep Learning Machine Learning and Transformers for Real-Time Protection
SN - 978-989-758-777-1
AU - Reddy P.
AU - Fahimuddin S.
AU - Hameed D.
AU - Allipeera D.
AU - Rajkumar V.
AU - Harshavardhan P.
PY - 2025
SP - 5
EP - 10
DO - 10.5220/0013875800004919
PB - SciTePress