B-YOND at Sharkfest Europe 2023

This repository contains the notebooks, code and documentation for B-YOND workshop "Unraveling the Packet Mysteries: A Wireshark Journey with Machine Learning!" at Sharkfest Europe 2023.

The data used in this workshop is kept in this separate repository.

Pre-Requisites

• A basic understanding of programming in Python
• Familiarity with Jupyter notebooks , if you haven't used Jupyter notebooks before please check this tutorial ahead of the workshop.

Workshop Material

There are two options to run this workshop:

• Option 1: (preferred): Using Google Colab

  Google Colaboratory, or "Colab" for short, is a cloud-based Jupyter notebook environment that allows for free Python code execution with free access to GPUs. To learn more about how to use Google Colaboratory, watch this YouTube tutorial.

  • Minimal setup required (5 mins)
  • Requires a google account

• Option 2: Local Mode

  • Requires local installation of prerequisites (tools & libraries)
  • Only supported on POSIX systems

  If you have a Windows machine either install and setup WSL2 ahead of time and make sure your network configuration is working as expected or switch back to Option 1

• Slide Deck is available for download on this link

Option 1: Using Google Colab

Step 1: Logging into Google Colab

• Go to Google Colab.
• Click on the Sign in button in the upper-right corner of the page.
• Sign in with your Google account credentials. If you don’t have a Google account, you will need to create one.

Step 2: Opening the first Notebook in Colab

• Click on File in the top menu.
• Select Open Notebook.
• In the pop-up window, go to the GitHub tab.
• Paste the following notebook URL into the provided field and press Enter or click Search.
  • https://github.com/b-yond-infinite-network/sharkfest-europe-2023/blob/main/notebooks/network-traces-clustering.ipynb
• Now, you can interact with and run the notebook in Google Colab.

Step 3: Opening the second Notebook in Colab

• Repeat Step 2 for the second notebook URL
  • https://github.com/b-yond-infinite-network/sharkfest-europe-2023/blob/main/notebooks/packet-anomaly-detection.ipynb

Option 2: Local Mode

Pre-Requisites

• POSIX compliant OS (Linux, MacOS, WSL2)
• Python 3.9 or above
• Make

Installation

If you do not have make installed you can check the Makefile being used and replicate the commands locally.

1. Clone the repo
2. Create a python virtual environment

   make .venv
   

3. Install required dependencies

   make install
   

4. Launch jupyter lab

   make launch
   

5. In your browser access the jupyter lab instance at http://localhost:8888/lab
6. Open any of the notebooks under notebooks/ folder and follow through the step by step in the notebook
7. To stop jupyter lab press Ctrl+C in the terminal where you launched jupyter lab or alternative use make stop
8. Once you are done if you wish to clean up your local filesystem run the following:

   make clean