Real-time Intrusion Detection Web App
Project III
Nguyễn Việt Hoàng - 20194434
About
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Real-time Intrusion Detection System implementing Machine Learning.
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We combine Supervised learning (RF) for detecting known attacks from CICIDS 2018 & SCVIC-APT datasets, and Unsupervised Learning (AE) for anomaly detection.
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System descriptive diagram:
Requirements:
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Windows OS.
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Python 3.9:
- link 64-bit: https://www.python.org/ftp/python/3.9.13/python-3.9.13-amd64.exe
- link 32-bit: https://www.python.org/ftp/python/3.9.13/python-3.9.13.exe
Note: select "Add Python 3.9 to PATH" in installation procedure.
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Npcap 1.71: https://npcap.com/dist/npcap-1.71.exe
Download project folder & environment setups:
git clone https://github.com/HoangNV2001/APT_Detection
cd APT_Detection
# Create a virtual environment
python3.9 -m venv venv
# Activate that virtual environment
source venv/bin/activate
# Install the project requirements.
python -m pip install -r requirements.txt
# or: pip install -r requirements.txt
Run program:
python application.py
Web app address: http://localhost:5000
Demo GUI
- Main page, overview of real-time captured flows:
- Flow detail page: