Adaptive Anomaly Detection System for Software Defined Networks

Tasks ( ⬜ - Not Started, 🟨 - Ongoing, 🟩 - Completed )

🟩 Topology creation with Mininet

🟩 RYU controller stats collection

🟩 Stats sending to Database

🟩 Dataset generation

🟩 WebPage design and integration

🟩 ML models research

🟩 Attack generation

🟩 Integrating ML models with RYU controller

🟩 Final tests

Environment

1. Ubuntu 20.04 LTS
2. mininet 2.3.0
3. ryu-manager 4.30

Prerequisites

1. Mininet emulation tool

sudo apt-get install mininet
pip3 install mininet

2. Python 3

sudo apt install python3

3. RYU controller

pip3 install ryu (OR) sudo apt install python3-ryu

4. Other dependencies

sudo apt-get install ffmpeg
sudo apt-get install netcat
pip3 install pymongo

5. Machine learning models:

• RBM (Restricted Boltzamann Machine)
• VAE (Variational Auto-Encoder)
• N-BEATS

Running the system

1. Run the RYU controller

ryu-manager [--verbose] ./path/to/your-app.py

2. Run mininet topology file

sudo python3 ./path/to/topology-file.py

The same is also implemented in BASH file 'run.sh'