Behavioral analysis of bitcoin users on illegal transactions

Abstract

Bitcoin is a popular crypto currency that is used as a mode of investment and a medium for trading goods and services. Anonymity, security and decentralization are significant features of Bitcoin. This creates several opportunities for criminals to involve in illegal and fraudulent activities. This research study aimed to automate the process of gaining the interconnected illegal transactions from Bitcoin Blockchain; which also identified the behavioral patterns and significant facts among illegal incidents that are of varied nature. The motivation for choosing this study was lack of literature that covers illegal incidents that are of various natures. In addition, the lack of literature on spending patterns common to several illegal incidents is also one of the motivations. For this study, an inductive approach was carried out. Initially the illegal incident and transaction data extracted from publicly available sources were parsed into BlockSci. In BlockSci scripts were written to gain the details on related illegal incidents. In visualizing the relationship of derived interconnected transaction indexes, Gephi tool was used in which the most significant indexes were summarized for further interpretation of data. Thereafter, traversing data back in the Blockchain was the method used in deriving patterns and significant facts. Finally, the common patterns obtained were evaluated based on previous findings. Consequently, the study recognized common spending patterns and popular exchanges used.