A cybersecurity and regulatory framework for mitigating fraud and illicit activity in cryptocurrency ecosystems

The worldwide cryptocurrency use has changed the world of digital finance but has also opened new opportunities to commit fraud and money laundering, as well as money laundering, and other financial offenses with the help of computers. Increasingly, decentralized designs, smart contract defects, and exchange weaknesses are used to launder black market trails of digital transactions by criminals. Regulatory blind spots created by lack of coherent oversight by Government agencies in the United States, including the Securities and Exchange Commission (SEC), Financial Crimes Enforcement Network (FinCEN), and Commodity Futures Trading Commission (CFTC) have been actively exploited by more advanced actors. This paper is suggesting a Cybersecurity and Regulatory Convergence Model (CRCM) that will help reduce fraud and illicit activity in cryptocurrency ecosystems. The study will use a mixed methodology that involves threat mapping, blockchain forensics, and regulatory gap analysis based on the data provided by Chainalysis (2018-2024) and the FinCEN enforcement reports. The model incorporates the use of AI-based anomaly detection, multi-signature wallet controls and risk-based compliance scoring into a single cross-agency monitoring architecture. The results show that more than 60 percent of illegal cryptocurrency exchanges now have stablecoin-linked addresses, which is a decisive change in typology in laundering. The integration of the financial regulation with cybersecurity engineering bolsters the fraud prevention, improves the anti-money laundering (AML) and Know Your Customer (KYC) compliance, and contributes to flexible coordination between the federal agencies. The framework proposed provides a technically informed and policy aligned roadmap of the protection of the integrity of digital asset markets- to support the twin goals of innovation and security in the decentralised financial ecosystem.