Heuristics for Detecting CoinJoin Transactions on the Bitcoin Blockchain

Hugo Schnoering, Michalis Vazirgiannis
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Abstract

This research delves into the intricacies of Bitcoin, a decentralized peer-to-peer network, and its associated blockchain, which records all transactions since its inception. While this ensures integrity and transparency, the transparent nature of Bitcoin potentially compromises users' privacy rights. To address this concern, users have adopted CoinJoin, a method that amalgamates multiple transaction intents into a single, larger transaction to bolster transactional privacy. This process complicates individual transaction tracing and disrupts many established blockchain analysis heuristics. Despite its significance, limited research has been conducted on identifying CoinJoin transactions. Particularly noteworthy are varied CoinJoin implementations such as JoinMarket, Wasabi, and Whirlpool, each presenting distinct challenges due to their unique transaction structures. This study delves deeply into the open-source implementations of these protocols, aiming to develop refined heuristics for identifying their transactions on the blockchain. Our exhaustive analysis covers transactions up to block 760,000, offering a comprehensive insight into CoinJoin transactions and their implications for Bitcoin blockchain analysis.
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在比特币区块链上检测CoinJoin交易的启发式方法
这项研究深入研究了比特币的复杂性,这是一个分散的点对点网络,以及它相关的区块链,它记录了自成立以来的所有交易。虽然这确保了完整性和透明度,但比特币的透明性可能会损害用户的隐私权。为了解决这个问题,用户采用了CoinJoin,这是一种将多个交易意图合并到一个更大的交易中以增强交易隐私的方法。这个过程使个人交易跟踪变得复杂,并破坏了许多已建立的区块链分析启发式方法。尽管它很重要,但在识别CoinJoin交易方面进行的研究有限。特别值得注意的是各种各样的coinjoinimplementation,如JoinMarket、Wasabi和Whirlpool,由于它们独特的交易结构,每个都呈现出不同的挑战。本研究深入研究了这些协议的开源实现,旨在开发精细的启发式方法来识别区块链上的交易。我们的详尽分析涵盖了高达76万笔的交易,为CoinJoin交易及其对比特币区块链分析的影响提供了全面的见解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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