CMixing: An Efficient Coin Mixing Platform to Enhance Anonymity in Cryptocurrency Transactions

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Abstract

Coin mixing methods are widely used to enhance anonymity in cryptocurrency transactions by obfuscating the linkages between recipients and senders. Specifically, coin mixing methods combine several users’ transactions into a CoinJoin transaction and decompose the original transactions’ outputs into a set of decomposed outputs with similar amounts. However, existing methods have two shortcomings. Firstly, CoinJoin transactions lack anonymity guarantees. Secondly, the number of decomposed outputs is not minimized. To tackle these two shortcomings, we develop a platform named CMixing for mixing transactions with anonymity guarantees and minimal fees. For a CoinJoin transaction obtained by CMixing, the probability of adversaries correctly guessing the original output of a decomposed output does not exceed 𝑐, where 𝑐 is a privacy requirement. Thus, the first shortcoming is solved. Additionally, CMixing uses an approximation algorithm to decompose original outputs, which approximately minimizes the number of decomposed outputs. Thus, the second shortcoming is solved. Our demonstration will showcase how users can use CMixing to make CoinJoin transactions. We will also show the fees saved and the level of anonymity achieved using our algorithm.