Authors: Gaurav A. Bagul, Parth P. Jadhav, Pratik S. Rahane, Assistant Professor Vipin K. Wani
Abstract: Cryptocurrencies have rapidly grown into a pop- ular medium of digital exchange, offering speed, security, and borderless transactions. While these benefits have driven global adoption, the pseudony- mous and decentralized nature of cryptocurrencies also makes them highly vulnerable to misuse in ille- gal activities such as money laundering, terrorism financing, and fraud. Recent reports highlight bil- lions of dollars being laundered annually through cryptocurrency channels, often using techniques like mixers, peel chains, and cross-chain transfers. Traditional Anti-Money Laundering (AML) sys- tems, designed mainly for conventional banking transactions, struggle to handle the complexities of blockchain-based transactions. They often func- tion as black boxes, providing risk scores without clear reasoning, and they are reactive rather than proactive in detecting suspicious activities. To address these challenges, the proposed sys- tem CryptoTrack: A Data-Driven System for De- tecting Cryptocurrency Laundering. The system leverages advanced analytics to identify suspicious accounts and transactions, while integrating Ex- plainable Artificial Intelligence (XAI) to provide transparent justifications for every detection. Un- like existing systems that only flag activities, Cryp- toTrack enables users and compliance officers to understand the exact reasons why a transaction is considered risky, thereby increasing trust and re- ducing false positives. A visualization dashboard further supports users by providing intuitive in- sights into detected suspicious activity. The proposed framework bridges the gap be- tween opaque detection models and the practical requirement for interpretability in financial mon- itoring. By combining data-driven detection, ex- plainability, and transparency, CryptoTrack offers a more reliable and effective approach to combating financial crimes in the rapidly evolving landscape of cryptocurrency.
