Code on phishing-site detection using Machine-Learning.
This code takes following as a input.
- URL from the address bar.
- Screen-shot of the current page.
Using these as inputs for the code the network test the data if the given URL is Legitimate or not.
This code is written with following language.
- UI designs are done using HTML,CSS and JS with the combination of Django framework.
- Training and testing of data are done using Python.
Following are the details about the file inside phishApp/PhishingSiteDetection
| File Name | Description |
|---|---|
| site_list.txt | These are the site details which you will be training the network for testing or for datasets |
| openBrowser.py | Code to open the sites listed inside site_list.txt to take screen shot of it and store it as a dataset |
| save_model.py | Code that is used to train the model (Updated the path based on your system) |
| screenshot.py | Used to take the screen shot of the browser page |
| load_models.py | Used to test the sample model |
Explore other files in phishingUrlDetectionUsingML
Run
python3 manage.py runserver
Explore other files in phishingUrlDetectionUsingML