DeCrypt: Revealing Anonymized Transactions

Cryptocurrencies like Bitcoin were designed to provide maximum anonymity, but the transparency and immutability of blockchain transactions have made deanonymization a significant research focus. Deanonymization involves identifying individuals behind pseudonymous addresses through methodologies such as transaction graph analysis, address clustering, IP tracking, and machine learning inference techniques. This paper explores these methodologies, emphasizing the role of privacy-augmenting technologies like coin-mixing services in countering deanonymization efforts. While deanonymization is essential for ensuring compliance with anti-money laundering (AML) regulations and facilitating crime investigations, it raises substantial privacy concerns. This study critically examines the trade-offs between privacy and security, discussing the legal, ethical, and technological implications of deanonymizing blockchain transactions. By addressing these considerations, the paper highlights the broader impact of deanonymization on financial innovation and regulation, aiming to balance privacy protection with security needs.