An AI-Powered Browser Extension Using Roberta and XAI for Phishing Email Detection and Security Awareness

Ahmed Murtaza, Ayesha Shahid, Safeer-ul-Hassan, Syed Masood Umar Rizvi, Saima Siraj
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Ahmed Murtaza, Ayesha Shahid, Safeer-ul-Hassan, Syed Masood Umar Rizvi, Saima Siraj: Department of Information Technology Quaid-e-Awam University of Engineering, Science and Technology Nawabshah, Pakistan

International Journal of Innovations in Science & Technology, 2025, vol. 7, issue 6, 97-106

Abstract: Phishing attacks are a common and serious cybersecurity threat today. They exploit human weaknesses by stealing sensitive information by sending fake emails and harmful links. Traditional email filtering systems like rule-based methods and black-box models, struggle to detect phishing. Rule-based filters fail when attackers use new tricks, and black-box models lack transparency, which limits user awareness.This work introduces a smart browser extension that uses deep learning and Explainable AI (XAI) for phishing detection. We use a transformer-based model, Roberta, trained on a large email dataset, achieving 98.12% accuracy in classifying email content. Forchecking URLs, we use VirusTotal, which gathers threat intelligence from multiple sources. We also apply XAI tools to highlight key parts of the text that contributed to the classification of the email content, and a large language model (LLM) to provide simple explanations about phishing.Our hybrid approach combines explainable deep learning with multi-source URL verification. This helps users understand phishing threats better and improves their ability to spot attacks on their own

Keywords: Phishing Detection; Cybersecurity Awareness; RoBERTa; Explanable AI; Deep Learning (search for similar items in EconPapers)
Date: 2025
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