IntruNetX-Realtime-Network-Intrusion-Detection-System

"Monitoring the unseen, securing the unknown."

IntruNet IDS is a lightweight real-time Intrusion Detection System (IDS) built using Flask, Scapy, and Machine Learning.
It captures live network packets, analyzes traffic flows, predicts potential intrusions, and allows the user to block/unblock suspicious IP addresses — all through a clean web dashboard.

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Screenshots

🔐 IntruNetX UI:

Features 🚀

• Real-time network traffic capture
• Flow-based packet feature extraction
• Machine Learning prediction (attack detection)
• Block and Unblock IPs dynamically
• CSV Export for captured traffic
• Responsive web dashboard with Bootstrap
• Lightweight and easy to run locally

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Technologies Used 🛠️

• Python 3.10+
• Flask (Backend Web Server)
• Scapy (Packet Sniffing)
• scikit-learn (ML Model for prediction)
• Bootstrap 5 (Frontend styling)
• HTML + JS (Frontend dashboard)

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Installation 📦

1. Clone the Repository

   git clone https://github.com/Rushi19-04/IntruNetX-Realtime-Network-Intrusion-Detection-System.git
   cd IntruNet-IDS

2. Install the required libraries

   pip install -r requirements.txt

3. Check/Install WinPcap/Npcap (For packet sniffing on Windows)

4. Place the Trained ML Model

   • Ensure model.pkl and scaler.pkl are inside the model/ directory.

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How to Run 🚀

1. Start the Flask server:

   python app.py

2. Open your browser and visit:

   http://127.0.0.1:5000
   

3. Use the Web UI to:

   • Start Capture
   • Stop Capture
   • Monitor Live Traffic
   • Block/Unblock IPs
   • Export Captured Data to CSV

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Project Structure 📂

IntruNet-IDS/
│
├── app.py                 # Main Flask Application
├── predict.py             # Machine Learning Predictor
├── model/
│   ├── model.pkl          # Pre-trained ML Model
│   └── scaler.pkl         # Feature Scaler
├── templates/
│   └── home.html          # Frontend Web Dashboard
├── static/                # (optional for css/js if extended)
├── captured_traffic.csv   # Exported CSV (after clicking export)
├── requirements.txt       # Python dependencies
└── README.md              # Project Documentation

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Requirements 🧪

• Python 3.10 or higher
• Flask
• Scapy
• scikit-learn
• pandas
• joblib
• numpy

(Already listed inside requirements.txt)

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Future Improvements 🌟

• Add automatic alerting/email notification on attacks
• Add graphs and visualizations (e.g., live traffic graphs)
• Support for offline PCAP file analysis
• Extended prediction with multiple attack categories
• Integrate deeper packet inspection

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Disclaimer ⚡

IntruNet IDS is meant for educational, research, and local network monitoring purposes only. Unauthorized scanning or interception of third-party networks without consent is illegal.

License

This project is licensed under the MIT License.

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Credits 🙌

Made with ❤️ by Rushikesh | Viraj | Devendra | Shubham