Decoding the dark: AI and ML in the dark web cybercrime and cryptocurrency forensics

Decoding the dark: AI and ML in the dark web cybercrime and cryptocurrency forensics

연구 분야: Safety

학회: International Cybersecurity Law Review

The study examines the digital forensics of cryptocurrencies and the dark web, explicitly focusing on the role of elements and tools, such as blockchain, computers, and mobile phones, in their formation and evidence gathering. It also explores using artificial intelligence and machine learning in dark web forensics. The descriptive-analytical method highlights the need for urgent research in digital cryptocurrency forensics, particularly in significant cryptocurrencies such as Monero, Ethereum, Verge, and Dogecoin, which are gaining popularity among legitimate and malicious users. The study also highlights a critical gap: the need for substantial research on host-based cryptocurrency forensics, especially mobile-based forensics. Most studies on host-based forensics focus on outdated operating systems or platforms, underscoring the need for research on more current versions. Security and vulnerability assessment studies are paramount for examining forensic methods for cryptocurrencies, as they can provide insights into potential exploits or attacks that can be instrumental in forensic investigations.