Since the interest in blockchain technology has risen in recent years, the number of cryptocurrencies has increased. Due to this, there is an increasing need to exchange currencies. Several companies offer services that solve this problem in different ways. The transfers they execute are called cross-blockchain transactions. This kind of exchanges occasionally produce two single transactions, which are saved on the blockchains of the involved cryptocurrencies. As these ledgers are distributed over public peer-to-peer networks, the transaction data can easily be retrieved and analyzed. However, exchange information linking two transactions to each other is not publicly visible.
This thesis aims to identify cross-blockchain transactions, by matching single transactions saved on the different blockchains. First, we analyze in detail the processes taken by an exchange service when executing a trade. Based on this, we determine heuristics and design a recognition algorithm. We implement this algorithm within a tool and evaluate its output. Finally, we show to what extent the identification of cross-blockchain transactions is feasible.
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