As far as we know, ĞMixer is the first libre alternative in the world for monetary mixing. Several points make it so original:
The source code and the protocol are under libre license (GNU AGPL), and the service can run on a distributed network: there is no central authority, and it is censorship-proof.
ĞMixer applies the onion routing communication technology (originally developed for Tor) to the money: instead of passing the transaction through one unique mixing account, it sends the transaction to an account, which resends it to another, and so on until the destination account. Each mixing node only knows the account it receives the transaction from and the one it sends the transaction to. It is necessary to corrupt each intermediary node to establish the link between sender and receiver.
ĞMixer works even if you do not trust any node in the network: before sending money into the mixer, the client asks each implied node for a signed document in which the node promises, when it receives the transaction, to send it to the specified account. If a malevolent node keeps the money or diverts it to a complicit acount, the client can publish the signed document and thus publicly discredit the node. Thanks to onion routing, publishing such a document does not threaten anonymity of transaction.
A discredited faulty node owner could create a new anonymous node, in order to bypass this security. By joining a ĞMixer network with a Web of Trust, we could demand that each node is connected to an existing identity. So the thief is not only an anonymous computer, but a living person, and theft becomes absolutely pointless.
A software implementing this protocol exists, ĞMixer-py (GitLab repository), developed in Python under GNU AGPL for the libre currency Ğ1. Of course, the project is transposable to any cryptocurrency.
A simulator (libre source code) which generates a traffic over a network, and to an analysis of obtained transactions, enables measuring the network's efficience and security, corresponding to the chosen parameters.
Graph above shows, for each transaction which got out of the network (reached its receiver), the standard deviation of the probabilities for each client which has possibly started it.
About this donation monitor
Collected money will enable to pay back contibutors and hosters.