Models and applications for the bitcoin ecosystem

Cryptocurrencies are widely known and used principally as a means of investment and payment by more and more users outside the re- stricted circle of technologists and computer scientists. However, like fiat money, they can also be used as a means for illegal activi- ties, exploiting their pseudo-anonymity and easiness/speed in mov- ing capitals. This thesis aims to provide a suite of tools and mod- els to better analyze and understand several aspect of the Bitcoin blockchain. In particular, we developed a visual tool that highlights transac- tion islands, i.e., the sub-graphs disconnected from the super-graph, which represents the whole blockchain. We also show the distribu- tions of Bitcoin transactions types and define new classes of non- standard transactions. We analyze the addresses reuse in Bitcoin, showing that it corresponds to malicious activities in the Bitcoin ecosystem. Then we investigate whether solids or weak forms of arbitrage strategies are possible by trading across different Bitcoin Exchanges. We found that Bitcoin price/exchange rate is influenced by future and past events. Finally, we present a Stochastic Model to quantitative analyze different consensus protocols. In particular, the probabilistic analysis of the Bitcoin model highlights how forks happen and how they depend on specific parameters of the protocol.