Shared Send Untangling in Bitcoin
Bitcoin is a widely used pseudo anonymous cryptocurrency. Information about all transactions is stored in the public domain, whereas connections between transacting entities in the Bitcoin network and corresponding real world entities are private. It is possible to reduce anonymity of the currency by analyzing history of operations and flow of funds using additional information (such as some facts that Bitcoin users have disclosed themselves) Therefore, additional measures to obfuscate transaction history (tangling) are popular among the network users. There are two basic approaches for such tangling: shared send and shared coin mixers. In the paper, the concept of shared send transactions untangling is formalized. We prove NPcompleteness of the shared send mixers detection problem and propose a number of practical modifications to the problem. Finally, we provide the results of our computational experiments to detect mixing schemes. (c) 2016 Bitfury Group Limited Without permission, anyone may use, reproduce or distribute any material in this paper for noncommercial and educational use (i.e. other than for a fee or for commercial purposes) provided that the original source and the applicable copyright notice are cited. crystal@bitfury.com, Bitfury Group Bitcoin is a widely used cryptocurrency supported by the eponymous decentralized network [1] The medium of exchange for Bitcoin is a payment unit with the same name. Bitcoins are transferred using transactions that utilize common cryptographic primitives (such as digital signatures and hash functions) to provide authentication capabilities. All transactions are included into a publicly available distributed ledger (the blockchain) after being verified by the nodes in the Bitcoin network. One of important properties of Bitcoin is its pseudonymity [2] Participants in the Bitcoin network are not obliged to disclose ownership of bitcoins; thus, data about the owners of bitcoins is generally not available. However, given the transaction history and data that Bitcoin users have disclosed about themselves, it may be possible to recover information about particular bitcoins. The uncovered information could be used for transaction risk scoring performed by Bitcoin financial services, during investigations by law enforcement, and in a variety of other applications. In order to counteract loss of privacy associated with blockchain analysis attempts, the Bitcoin community has developed additionalmethods of ensuring pseudonymity. Thesemethods are referred to asmixing or transaction tangling, as they operate by tangling, or mixing transaction histories from multiple sources. Thus, relationships among real world entities owning addresses are obfuscated. Two main approaches can be distinguished among the existing tangling techniques: Shared coin services. Bitcoins are sent to an account of an intermediary service. After some time has passed, the service sends other available funds to the recipient's address. The process of sending to and reception from the intermediary is usually divided into several transactions. A client needs to trust the service; on the other hand, if operation was completed successfully, the connection between the sending and receiving addresses is almost impossible to trace. Shared coin services can be provided by exchanges or services without registration depending on the desired degree of anonymity. Shared send. Users organize into groups (via an intermediary) and tangle their coins in a single transaction (e.g. within the framework of the CoinJoin algorithm [3] The small set of senders and recipients may be known, but it is not clear how the funds are distributed among them. In this paper, we concentrate on the analysis of shared send mixers, which can be defined as two related problems: How to determine whether a certain bitcoin transaction is a result of a shared send operation How to uncover value flows within shared send transactions. Detecting and analyzing shared send mixing is an important problem for the entities engaging in blockchain analysis and/or research on blockchain privacy issues. Since shared send mixing is more tractable than shared coin mixers from theoretical and computational standpoints, it could be a good starting point for blockchain analysis in general. Previous research. There are a number of academic papers studying the anonymity properties of the Bitcoin network. F. Reid et al. [4] present general ideas about tracking bitcoin flows in the network