Date and Time:
Tuesday, April 1, 14:00-16:00
Learning Objectives:
Participants will leave the workshop equipped with practical, applicable skills in creating interactive Jupyter Notebooks for forensic data analysis. Specifically, they will:
• Acquire hands-on experience in using an interactive user interface in Jupyter Notebooks.
• Learn to utilize Jupyter Widgets to enhance evidence data visualization, manipulation, and exploration.
• Know how to set up and customize an analytical environment for individual use and collabo-rative team workflows and how to integrate existing analytical and data processing tools.
Experience Level:
Average. Participants are expected to have a basic knowledge of Python programming and an understanding of common analytical tools (e.g., Bash, Volatility, etc.).
Description:
The workshop delves into the power of Jupyter Notebooks as an intuitive and interactive platform for digital forensic analysis, highlighting their capability for rapid iteration and prototyping of analytical workflows. Through hands-on exercises, participants will learn to utilize Jupyter Widgets to create dynamic, customizable interfaces that enhance data visualization, exploration, and manipulation. The session includes step-by-step guidance on setting up an analytical environment, a demonstration of real-world examples of forensic workflows in Jupyter Notebooks, and the creation of an interactive Notebook for data analysis in a realistic scenario. By the end of the workshop, attendees will be able to design and prototype advanced forensic workflows, seamlessly integrate existing analytical tools, and elevate both individual and team-based investigations with innovative, interactive approaches.
Preparation Details:
Participants will have access to a remote virtual server using JupyterHub, which can be accessed through a web browser. Local deployment of training examples will also be possible. In this case, participants must have installed Python and a suitable code editor (preferably Visual Studio Code with Python and Jupyter extension).
Tutorial Web: