Paper: arXiv 2311.12491

Authors: Hugo Schnoering, Michalis Vazirgiannis

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.

Complexity vs Empirical Score

  • Math Complexity: 2.5/10
  • Empirical Rigor: 7.0/10
  • Quadrant: Street Traders — practical and empirical, lighter on theory

Why this score: This paper presents a strong empirical analysis of Bitcoin’s CoinJoin transactions across major implementations up to block 760,000. While mathematical complexity is minimal, the heuristic-based approach provides practical value for blockchain forensics and privacy research.

Research Flowchart

  flowchart TD
    A[Goal: Develop Heuristics to Detect CoinJoin Transactions] --> B[Input: Bitcoin Blockchain Data up to Block 760,000]
    B --> C[Analyze Codebases of JoinMarket, Wasabi, & Whirlpool]
    C --> D[Identify Unique Transaction Structure Patterns]
    D --> E[Formulate Implementation-Specific Heuristics]
    E --> F[Outcome: Accurate Identification & Mapping of CoinJoin Activity]

Cited References (7)

  1. Bitcoin: A peer-to-peer electronic cash system (2008)
  2. A fistful of bitcoins: characterizing payments among men with no names (2013)
  3. Pinpointing and measuring wasabi and samourai coinjoins in the bitcoin ecosystem (2021) — link
  4. Dumplings (2023)
  5. ZeroLink: The Bitcoin Fungibility Framework (2017)
  6. Wabisabi: Centrally coordinated coinjoins with variable amounts (2021)
  7. Improving Cryptocurrency Crime Detection: CoinJoin Community Detection Approach (2023)

0 of 7 cited works are in the corpus; resolved via arXiv source bundles, Semantic Scholar and OpenAlex. Corpus-wide: 2518 linked papers.