
Abstract
The dark web poses significant challenges to digital forensic investigations due to its anonymous nature and the sophisticated encryption technologies employed by its users. This paper explores the potential of Generative Pre-trained Transformer (GPT) tools and other AI methodologies to enhance forensic practices on the dark web. Employing a mixed-methods approach that includes experimental applications and qualitative analyses, this study investigates the capabilities of AI-driven tools in improving the accuracy and efficiency of digital forensics. Our results demonstrate notable advancements in forensic processes, with AI tools providing deeper insights and faster processing of complex data sets. The paper concludes by discussing the transformative impacts these technologies have on dark web investigations, opening new avenues for both practice and research in cybersecurity forensics.
Introduction
The internet’s growth over the decades has given rise to an intricate landscape harboring covert domains trafficking in unlawful activities. Among these domains, the dark web stands out as an enigmatic realm where anonymity prevails and nearly anything goes. Digital forensics experts employ specialized knowledge and advanced technological tools to dive into the corners of the dark web where criminal activity happens (Tolman, 2023). This study aims to evaluate the effectiveness of AI and GPT tools in digital forensics investigations on the dark web, focusing on their potential to improve accuracy, efficiency, and outcome predictability in forensic examinations.
Background Information
The dark web is a fraction of the deep web, accessible only through specific anonymizing software like Tor, which obscures users' identities and....