An Explainable Multi-Modal Phishing Detection Framework

Abstract

Phishing is one of the most common online threats, and it is becoming harder to detect because attackers use AI nowadays, fake website designs, and new tricks. Traditional methods like simple rules or URL reputation checks are no longer enough to stop these modern attacks. This report introduces Phishing Shield AI, a phishing detection system that uses three types of analysis: text analysis with NLP, URL and domain checking, and computer vision to compare webpage visuals. Each part gives a risk score, and the system combines them to decide whether something is phishing. It also provides clear explanations by showing which words, links, or images look suspicious. Based on the literature review, gap analysis, system design, and evaluation, the multi-modal approach improves accuracy, reduces mistakes, and adapts better to new phishing methods. Overall, Phishing Shield AI is a practical and scalable solution that performs better than single-method systems and has strong potential for future improvement.