AI-Powered Phishing Attack Real Time For User Proctection
This research paper presents PhishShield AI, a hybrid and explainable phishing detection system designed to address the growing challenges of modern cyber threats. The system combines rule-based heuristic analysis with machine learning and natural language processing techniques to accurately detect phishing attacks in real time. Unlike traditional approaches that provide only binary results, the proposed system focuses on Explainable Artificial Intelligence (XAI), offering clear and human-readable explanations that help users understand the nature of detected threats.The system analyzes URLs, email content, and web pages by examining structural patterns, textual features, and hidden elements such as malicious forms. It integrates multiple detection layers to improve accuracy and ensure reliable performance, even against zero-day phishing attacks. Additionally, the inclusion of a user-friendly interface and a gamification component enhances user engagement and promotes cybersecurity awareness.Overall, this work aims to provide an effective, accessible, and intelligent solution that not only improves phishing detection but also educates users, enabling them to make safer decisions in the digital environment
Authors
- Hardik Chavan
Institutions
- MIT Art, Design and Technology University (IN)
Publication Details
- Journal
- Zenodo (CERN European Organization for Nuclear Research)
- Published
- 2026-04-28
- DOI
- https://doi.org/10.5281/zenodo.19862959
- Primary Topic
- Spam and Phishing Detection
- Type
- article
- Field-Weighted Citation Impact
- 0.00