From scams to ransomware attacks, law enforcement agencies have documented numerous criminal cases on Bitcoin over the years. In 2023 alone, reported ransomware cases reached 5,070, marking a dramatic 55.5% increase compared to the previous year. Additionally, dark web marketplaces such as Silk Road, AlphaBay, and Hansa have become infamous for using Bitcoin as a primary form of payment for illegal goods like weapons, drugs, and counterfeit documents. The core issue lies in the pseudo-anonymity Bitcoin offers, which complicates the process of tracing transactions back to individuals and hinders law enforcement efforts to hold criminals accountable. Despite the rise in cryptocurrency-related crime, a reliable solution for deanonymizing these transactions remains elusive.

With the growing threat of financial cybercrime, law enforcement agencies are urgently seeking effective methods to unmask the identities of these criminals. Researchers are actively investigating approaches like deanonymization, which studies transaction patterns on cryptocurrency networks to link them to real-world identities. The primary objective of this thesis is to develop a program for law enforcement that monitors and analyzes Bitcoin network data, estimating the origin IP addresses of transactions by using the methodology described by Biryukov and Tikhomirov in a previous study. This program serves as a valuable tool in combating the misuse of cryptocurrency's privacy features.