phishingdetection

A machine learning-based system that detects phishing websites by analyzing URL, domain, and HTML-based features. Compares 9 ML models — with Gradient Boosting achieving 97.4% accuracy — to classify URLs as phishing or legitimate.

Phish Guard is an intelligent phishing detection system that identifies malicious URLs and websites in real time, helping users stay safe from online scams and cyber threats.

Fsociety Phishing Blocker fsociety Phishing Blocker is a browser extension designed to safeguard users from phishing attacks by identifying and blocking malicious URLs in real time.

AI-powered cybersecurity platform for detecting phishing emails, scam websites, fake job postings, and online threats.

Developed a CyberGuard AI assistant that detects phishing attempts and monitors potential cybersecurity threats using AI-driven analysis. The system analyzes suspicious emails and links to alert users and enhance overall security. It demonstrates the practical application of AI in threat detection and cyber defense.

An ML-based system to detect phishing websites using URL and domain analysis. Includes Source Code, PPT, Synopsis, Report, Documents, Base Research Paper & Video tutorials.

Machine learning based phishing email detector using Random Forest and TF-IDF with custom feature engineering.

A 7-layer phishing website detector Firefox extension with ML scoring.

Cybersecurity project for detecting suspicious URLs and phishing indicators.

Phishing attacks are a significant threat to online security, targeting individuals and organizations by tricking them into revealing sensitive information. Project Includes Source Code, PPT, Synopsis, Report, Documents, Base Research Paper & Video tutorials

This project aims to develop a machine learning-based system for detecting spam emails. Email Spam Detection Project With Code, Documents, PPT, Report and Video