Digital Investigations: Navigating Challenges in Tool Selection for Operating System Forensics

Abstract

The process of gathering, identifying, extracting, and documenting electronic evidence for use in
court is known as "digital forensics." We have a lot of tools at our disposal to make this procedure
quick and straightforward. Four tools have been selected for investigation and analysis in this work.
For every kind of digital forensics, the top tools have been selected based on several criteria. For
computer forensic tools, (Stellar and Forensic Tool Kit) have been investigated; for network forensic
tools, Network Map has been selected, and OSF mount has been examined as a live forensic tool.
Other forensic tool types, such as database, operating system, and mail forensic tools, are also
covered in this work. The role of Artificial intelligence in Digital Forensic tools has been discussed
in this paper by using both Decision Stump and Bayes net machine learning techniques. After
making an investigation of the IoT device traffic dataset using these two techniques, Decision Stump
gives us less accurate results compared with Bayes net.