Hybrid Machine Learning Model For Efficient Botnet Attack Detection In IoT Environment

This project implements a hybrid machine learning model designed to detect botnet attacks within Internet of Things (IoT) environments efficiently.

Project Structure

• BACKEND: Contains the backend logic and model handling.
• FRONTEND: Contains the user interface and application logic (e.g., app.py).
• Models: Includes pre-trained models such as ANN, CNN, LSTM, RNN, DNN

Key Features

• Efficient Detection: Uses a hybrid ML approach to identify threats.
• IoT Optimization: Tailored for the constraints and nature of IoT network traffic.
• User Interface: Provides a frontend for interaction and visualization.

Getting Started

1. Navigate to the FRONTEND or BACKEND directory to experiment with the components.
2. Review the app.py in FRONTEND for the main application entry point.