Research Area:  Digital Forensics

Abstract:

The digital forensic tool plays a crucial role in protecting from share trading fraud, financial fraud, identity theft, and money laundering. Investigators in Digital Forensic analysis have the right to use various forensic tools for investigation. Regretfully, several contemporary digital forensics technologies are lacking in a number of areas. The research aims to study different phases of digital forensic methods and various issues encountered during the investigation process. In addition, the study also focuses on the mindful analysis of different kinds of digital forensic tools. The methodology includes building, providing defense to any scene, proper review, effective communication, and identification. It also involves the identification of the digital investigation opportunities and recognizing all the policies for controlling proof. The tools and procedures that can be utilized to investigate digital crime are discussed in this article. Desktop forensic tool, Live Forensic tool, Operating System Forensic tool, and Email Forensic tool are some of the covered categories. AI-based network logs are evaluated using a variety of machine learning techniques and compared with various metrics such as accuracy, precision, recall, and F1-Score. A comparative analysis of popular tools in each category is tabulated to understand better, making it easy for the user to choose according to their needs. Furthermore, the paper presents how machine learning, deep learning, and natural language processing, a subset of artificial intelligence, can be effectively used in digital forensic investigation. Finally, the future direction of the challenges and study scope in digital forensics and artificial intelligence is also mentioned for potential researches.

Keywords:  

Author(s) Name:  Kousik Barik, A. Abirami, Karabi Konar & Saptarshi Das

Publisher name:  Springer

DOI:  10.1007/978-3-030-93453-8_4

Volume Information:  pp 71–95

Paper Link:   https://link.springer.com/chapter/10.1007/978-3-030-93453-8_4