The proliferation of dark web marketplaces has exacerbated illegal trade, particularly in narcotics, facilitated by Bitcoin’s pseudo-anonymous nature, which complicates transaction tracing and enables widespread illicit use. These platforms exploit the anonymity of the dark web and Bitcoin’s untraceability, posing significant regulatory challenges. Recent research has focused on analyzing Bitcoin-related criminal activities, including dark web transactions, Ponzi schemes, money laundering, and fraud. This study systematically investigates the operational mechanisms of dark web marketplaces and conducts targeted monitoring of a specific platform. Over a three-month period, Bitcoin transaction data was collected through active engagement and analyzed using machine learning-based detection methods. The proposed approach demonstrated high efficacy, achieving a true positive rate of 98.9% and a false positive rate of 4.9%. Furthermore, financial flow analysis revealed the platform’s transaction volume totaled approximately 17 million RMB between November 11, 2023, and January 7, 2024, with detailed tracing of fund sources and destinations. The findings highlight critical methodologies for monitoring and regulating illicit Bitcoin activities on dark web markets.