I'm very happy to announce that we just released the first version of ds4n6_lib, the Data Science Forensics (DS4N6) Library!
9 months later, after many many hours of thinking, re-thinking and coding (over 10.000 lines of code now), we have created a first usable version of the library, although still in Alpha/Beta (depending on the modules).
In a nutshell, what we wanted to do in this release was to create a Jupyter-based forensic analysis environment so similar to traditional forensic tools, that forensicators do not really see a difference between this new environment and any other tool. We have therefore focused on creating a few easy to remember "commands" (Core Functions), most of them GUI based, and hiding the underlying complexity as much as possible.
This means that what you will see at first sight will be a set of GUI functions that allow you to analyze data very similarly to any other forensic tool you are used to.
BUT, that is only the bait! Now that your forensic data is on Jupyter and you are no longer afraid of it, an unprecedented analysis power opens to you, even if you still don't know it. Once in Jupyter, you will have the possibility to flexibly analyze massive amounts of data at blazing speed, easily do amazing visualization, run machine learning algorithms in your forensic data, and much more. That will be the next stage of your trip! For now let's just focus on getting familiar with the basics of the ds4n6_lib.
If you are not familiar with what the DS4N6 Library (ds4n6_lib) is or how it can help you, please check this blog post.
For further information check the Documentation section, where you will find resources about everything you need to know about the ds4n6_lib (overview, download & installation, foundations, cheatsheet, etc.).
If you want to start playing with it right away, just check this blog post (in the Cloud, in minutes, no registration or infrastructure needed).