Real-Time Phishing Website Detection Using Web Scraping and Machine Learning

Our project is geared towards developing a robust system for identifying phishing websites. This will involve scraping URL data, extracting key features and employing an unsupervised machine learning classifier to pinpoint suspicious URLs.

Key project components:
- Web Scraping: Collecting URL data from public datasets.
- Feature Extraction: Identifying and extracting relevant characteristics from the URLs. Key features to be considered include domain age, presence of IP address in URL, and number of subdomains.
- Real-Time Detection: Implementing a system for immediate identification of phishing threats.

Tech Stack:
- Back-end: Python, Machine Learning Model
- Front-end: Tailwind CSS, Flask

Ideal candidates for this project should have:
- Proficiency in Python and experience with machine learning
- Skills in web scraping and feature extraction
- Knowledge of using Tailwind CSS and Flask for front-end development
- Experience working with public datasets
- Understanding of key URL features related to phishing detection