Privacy in Bitcoin through decentralized mixers
In cryptocurrencies such as Bitcoin, the anonymity of the users may be compromised in many ways. In this thesis, we review the literature concerning existing protocols used to increase anonymity by a method called mixing and produce a classification for such protocols. We propose a decentralized synchronous N-to-N mixing model that takes into account many considerations of mixers. We address two frameworks within this model, the transaction blueprint and the network of transactions, the second approach being a new contribution. We explain how it functions and analyse its efficiency in the current Bitcoin ecosystem.
Bitcoin anonymity privacy mixer ecash cryptocurrency network