• address classification
• Bitcoin
• ransomware funds tracing
• taint analysis
• web scraping

The objective of the thesis was to analyze ransomware criminals operations in the Bitcoin ecosystem to discover common patterns in the money laundering process. Several Transaction graphs related to ransomware seed addresses were analysed by tracing counterfeit funds with the help of taint analysis techniques, using classifiers to deanonymize any Privacy Enhancing Technologies (PET) used to mask the origin of the funds. The analysis consists of graph creation, taint analysis and graph pruning, and path analysis. Resulting size of the incriminated graph, maximum laundering time of the funds, and type and number of PET services involved are analyzed for each path identified.