Advanced Intrusion Detection and Prevention System (Advanced_IDPS)

An intelligent and secure Intrusion Detection and Prevention System (IDPS) built using machine learning techniques on the NSL-KDD dataset. This project detects and prevents network-based cyberattacks in real time with a web interface.

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🔒 Features

• 🚀 Machine Learning-based threat detection
• 📊 Trained on NSL-KDD dataset (2025)
• 🌐 Web dashboard using Flask
• 📝 Real-time logging of detected threats
• 📁 Model persistence using joblib

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🧠 ML Model Training

• File: IDPS_Train_Model.ipynb
• Dataset: NSL-KDD-2025
• Libraries: scikit-learn, pandas, joblib

Trains and evaluates various models to identify anomalies in network traffic.

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🌐 Web Application

• Entry point: app.py
• Templates: templates/
• Static files (CSS/JS): static/
• Frontend: Simple UI to upload logs and see detection results.

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⚙️ Installation

# Clone the repository
git clone https://github.com/yourusername/advanced-idps.git
cd advanced-idps

# Create virtual environment
python -m venv venv
source venv/bin/activate      # On Linux/Mac
venv\Scripts\activate         # On Windows

# Install dependencies
pip install -r requirements.txt

🚀 Running the App
# Activate environment and run Flask app
python app.py




📚 Dataset
NSL-KDD 2025 is an improved version of the classic KDD Cup 1999 dataset.
Includes labeled records for DoS, Probe, R2L, and U2R attacks.

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🤝 Contributors
Thammisetti Sreenivasulu
Cybersecurity Intern | B.Tech in CSE - Cybersecurity
GitHub: Sreenivas-147

📬 Contact
For questions or contributions, reach out at:
📧 sree.tham147@gmail.com