Phishing Link Detection with Legitimate Website Verification

Author(s)	Alisha Vaishnav, Namrata Pakhare, Kunal Deore, Chinmay Kamodkar, Prof. Swapnil Patil
Country	India
Abstract	Phishing attacks remain one of the most common threats on the internet today. Many existing systemscan detect suspicious links, but they often stop at just giving warnings. This paper presents a practicalapproach that not only detects phishing URLs using a Random Forest model but also guides users bysuggesting legitimate alternatives. The system is designed to be simple, efficient, and helpful foreveryday users. Experimental results show strong performance, making it suitable for real-worldapplication
Keywords	Phishing Detection, Machine Learning, Random Forest, URL Analysis, Cybersecurity, Flask, Website Verification
Field	Computer > Network / Security
Published In	Volume 8, Issue 4, July-August 2026
Published On	2026-08-16

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