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PhishShield: A Multi-Modal AI-Based Anti-Phishing Detection Platform
Subject area: Science,Engineering and Technology · Area of research: Cyber Security and Safety
Abstract
Phishing is a trick in which a fake website pretends to be a real one, such as a bank, to steal a person’s password or money. Many existing tools check only one thing, such as whether a link appears on a blacklist. A new fake site that is not yet listed can pass such a check. This paper proposes PhishShield, a platform that studies a website through five separate channels: the URL text, the HTML code of the page, the SSL certificate, the domain registration record (WHOIS), and a screenshot of the page. Each channel gives its own risk score between 0 and 1. A weighted sum then combines these scores into one final score. If the final score crosses a set limit, the user sees a warning and the event is saved in a log. The system is built as small separate services using FastAPI, so that each part can be changed without touching the others. This is a design paper. Testing is planned and is described in the Future Work section.
Keywords
browser extension; late fusion; phishing detection; weighted scoring; web security
References
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How to cite this paper
@article{1724525,
author = {Gowdhami K, Rupika S, Darshini U M, Naviesh R P, Panchalarajan R},
title = {PhishShield: A Multi-Modal AI-Based Anti-Phishing Detection Platform},
journal = {Iconic Research And Engineering Journals},
year = {2026},
volume = {10},
number = {5},
pages = {342-347},
issn = {2456-8880},
url = {https://www.irejournals.com/formatedpaper/1724525.pdf},
abstract = {Phishing is a trick in which a fake website pretends to be a real one, such as a bank, to steal a person’s password or money. Many existing tools check only one thing, such as whether a link appears on a blacklist. A new fake site that is not yet listed can pass such a check. This paper proposes PhishShield, a platform that studies a website through five separate channels: the URL text, the HTML code of the page, the SSL certificate, the domain registration record (WHOIS), and a screenshot of the page. Each channel gives its own risk score between 0 and 1. A weighted sum then combines these scores into one final score. If the final score crosses a set limit, the user sees a warning and the event is saved in a log. The system is built as small separate services using FastAPI, so that each part can be changed without touching the others. This is a design paper. Testing is planned and is described in the Future Work section.},
keywords = {browser extension; late fusion; phishing detection; weighted scoring; web security},
month = {November},
}