AI FIREWALL

Phoenix is a project focused on DDoS detection, continuous learning, and human review workflows. It includes backend machine learning models, frontend web applications, and datasets for training and prediction.

Folder Structure

• dataset/
  Contains datasets for training, review history, and synthetic traffic data.

  • ddos_central_dataset.json — Main dataset for DDoS detection.
  • ddos_intermediate.json — Intermediate processed dataset.
  • ddos_review_history.json — Human review history.
  • synthetic_traffic.csv — Synthetic network traffic data.

• htil/
  Human-in-the-loop (HTIL) system for DDoS detection.

  • backend/ — Python scripts for continuous learning and human review.
    • ContinuousLearning_DDoS.py — Continuous learning pipeline.
    • HumanReview_DDoS.py — Human review workflow.
    • train_lstm.py, train_xgb.py — Model training scripts (LSTM, XGBoost).
    • requirements.txt — Python dependencies.
  • frontend/ — React web app for HTIL interface.
    • public/, src/ — Standard React structure.

• models/
  Pre-trained models and scalers.

  • lstm.pt — LSTM model (PyTorch).
  • model.pt — Additional model file.
  • scaler.joblib — Scaler for preprocessing.
  • xgb.joblib — XGBoost model.

• prediction/
  Prediction service for DDoS detection.

  • backend/ — Python server for ML predictions (ServerML_DDoS.py).
  • frontend/ — Vite/React web app for prediction interface.
    • public/, src/ — Standard Vite/React structure.
    • components/FirewallDemo.jsx — Demo component for firewall simulation.

Getting Started

Backend Setup

1. Navigate to the backend folder (e.g., htil/backend or prediction/backend).
2. Install Python dependencies:

   pip install -r requirements.txt

3. Run backend scripts as needed:

   python ContinuousLearning_DDoS.py
   python HumanReview_DDoS.py
   python ServerML_DDoS.py

   Double click on run_admin.bat to run ServerML_DDoS.py

Frontend Setup

1. Navigate to the frontend folder (e.g., htil/frontend or prediction/frontend).
2. Install Node.js dependencies:

   npm install

3. Start the development server:

   npm run dev

Usage

• Train models using scripts in htil/backend.
• Use the HTIL frontend for human review and continuous learning.
• Deploy prediction backend and frontend for real-time DDoS detection.

Dashboard

https://phoenix-dashboard-9cxm.onrender.com/