It is awful to say that the same technology is being misused by cybercriminals. Thus, in a broader sense, we need to be advanced regarding the technologies and apply them to have a vision of an eagle while using the internet. Hence, advances in cybersecurity became top priority nowadays.
So,this triggered interest in our team to develop a web-based application to deal with cybercrimes.
We focused on Botnet Detection and Phishing Detection as they have the more availing risk of harming.
This web page runs the Random Forest Algorithm and Decision Tree Classifier based model in the backend via flask App
Table of Contents
Depenedencies Python 3, Pandas, Numpy, Seaborn, MatplotLib, Sklearn, flask
URL - Phishing Detection (PhishingDetection.py, FeatureExtraction.py) Twitterbot Detection (mainpgm.py) Whole flask app code - server.py
TwitterBotnet deployed on cloud through Heroku and Git: https://detecttwitterbot.herokuapp.com/
HTML codes in templates folder
Furthur work:Updates in project by improving model furthur in regard of botnet detection!
Thank you for visiting this repository and looking at this project. Please feel free to contribute and take our analysis further.