Trawaler Phishing Website Detection

This literaly detect Phishing websites using Machine Learning and automaticaly warn it to user.

How it Works?

Extension detect all URLs browsing by user and check is they ar in white list. If not, extension send requet to the flask server and waiting for the server response.

Flask server capture POST request URLs and predict whether is it Phishing or not with trained ML Model and send result back to the client.

Extension catch the response from server and, if it is Phishing URL, extention load phishing warning. Also it allows to users to create white list.

This work with most of all the websites.

This support English and Sinhala Languages.

Chrome website with English Language.

Microsoft Edge with Sinhala Language.

What languages used?

Basicaly here used two languages,

• Python - for building ML Model and Server Backend
• JavaScript - for Chrome Extension

What inside the Code?

This contain with three major parts,

• Phishing URLs Detecion Machine Learning Model
• Server Side Backend for serve Extension Request
• Chrome Extension in Client Side

Building Machine Learning Model

Used Libraries -

tensorflow	numpy	pandas
urllib	re	ipaddress
bs4	whois	request
datetime	request	sklearn
matplotlib	keras

• Data downloading and creating Comma Seperated Value(.csv) Files

• Data Cleaning and Feature Extraction of Phishing URLs

• Data Cleaning and Feature Extraction of Legitimate URLs

• Creating Final Dataset and save in to Comma Seperated Value(.csv) Files

• Finding Best Machine Learining Model based on score

• Train best Machine Learning Model

Backend Server (Flask Server)

Used Libraries -

urllib	ipaddress	re
bs4	whois	urllib
datetime	requests	flask
feature	tensorflow	numpy

• Request Handler
• URL Checker

Trawler Browser Extension

• Extension

Resources

Feature Extraction Resource - Phishing-Website-Detection-by-Machine-Learning-Techniques