Harnessing Digital Strategies to Combat Cryptocurrency-Enabled Crimes: Addressing Money Laundering, Illicit Trade, and Cyber Threats

Chamunorwa Chitsungo ()

American Journal of International Relations, 2024, vol. 9, issue 7, 77 - 106

Abstract: Purpose: This research explores how advanced digital strategies can be harnessed to combat cryptocurrency-enabled crimes, focusing on the use of blockchain analysis, artificial intelligence (AI), machine learning, and enhanced regulatory frameworks to detect, trace, and prevent illegal transactions on cryptocurrency platforms. Materials and Method: The study examines the challenges law enforcement and regulatory bodies face due to the pseudonymous nature of cryptocurrencies and their cross-border complexities. It analyses emerging digital tools that facilitate the de-anonymization of transactions and enable real-time monitoring of suspicious activities. Case studies from recent high-profile cryptocurrency crimes, such as the Silk Road shutdown and recent ransomware attacks, are utilized to highlight the effectiveness of these digital strategies. Findings: The findings indicate that a multi-layered approach, which combines technological innovations with global regulatory efforts, is essential for mitigating risks associated with cryptocurrency as a facilitator of cybercrime. Advanced analytics and regulatory techniques are identified as key resources for detecting and preventing illicit activities. Implications to Theory, Practice and Policy: The research demonstrates practical implications for law enforcement agencies in developing strategies that integrate advanced digital tools to improve their capabilities to manage and investigate cryptocurrency-related crimes. From a policy perspective, the study highlights the importance of creating adaptive regulatory frameworks that can evolve alongside cryptocurrency technology to effectively address the unique challenges it presents in combating cybercrime.

Keywords: Cryptocurrency D74; Cybercrime K42; Blockchain Analysis O33; Artificial Intelligence L86; Machine Learning H11; Regulatory Frameworks D80 (search for similar items in EconPapers)
Date: 2024
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