Master's Thesis : BitCoin Clustering: a CoinJoin Discarding Heuristic

Abstract

The Bitcoin, which was an attempt to propose an alternative to the centralized currencies, quickly attracted all sorts of trafficking activities. The pseudo anonymity of the transactions and the absence of regulatory authority is a windfall for criminals.

Therefore, understanding and being able to extract exploitable information from the Bitcoin network is the key to deal with these illicit activities. There exist many techniques to extract exploitable information from the public transaction data. Unfortunately, many techniques have been deployed to counter them. This Thesis proposes a review of the application layer of the Bitcoin and of the work that has already been achieved in this field. Finally, a new clustering heuristic is proposed. In particular, an algorithm is presented to retrieve the public keys involved in a transaction. We will see how the graph theory and these keys can help to spot and discard the transactions that may result from an obfuscation technique.

Amongst other main contributions, it is shown that i) the popular transaction patterns vary extremely over time, ii) at least 3\% of the transactions involve several entities. Finally, iii) most of the clusters are very ephemeral, iv) and the wealth is by far non-uniformly distributed amongst them.