Analysis of CryptoNote Transaction Graphs Using the Dulmage-Mendelsohn Decomposition

Author Saravanan Vijayakumaran

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Saravanan Vijayakumaran
  • Department of Electrical Engineering, Indian Institute of Technology Bombay, Mumbai, India


We thank Justin Ehrenhofer for sharing the blockchain databases of the (no longer operational) Monero Original, MoneroV, Monero v7, and Monero v9 forks. We also thank him for his feedback on an earlier version of this paper, which helped improve the presentation of the empirical results. We thank Zuoxia Yu for sharing the full version of their FC 2019 paper. Finally, we thank the anonymous reviewers of PoPETs 2022 (where an earlier version of this paper was eventually rejected) and of the current conference for their comments. We prepared the instructions for reproducing our empirical results on the suggestion of a PoPETs 2022 reviewer.

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Saravanan Vijayakumaran. Analysis of CryptoNote Transaction Graphs Using the Dulmage-Mendelsohn Decomposition. In 5th Conference on Advances in Financial Technologies (AFT 2023). Leibniz International Proceedings in Informatics (LIPIcs), Volume 282, pp. 28:1-28:22, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)


CryptoNote blockchains like Monero represent the largest public deployments of linkable ring signatures. Beginning with the work of Kumar et al. (ESORICS 2017) and Möser et al. (PoPETs 2018), several techniques have been proposed to trace CryptoNote transactions, i.e. identify the actual signing key, by using the transaction history. Yu et al. (FC 2019) introduced the closed set attack for undeniable traceability and proved that it is optimal by showing that it has the same performance as the brute-force attack. However, they could only implement an approximation of the closed set attack due to its exponential time complexity. In this paper, we show that the Dulmage-Mendelsohn (DM) decomposition of bipartite graphs gives a polynomial-time implementation of the closed set attack. Our contribution includes open source implementations of the DM decomposition and the clustering algorithm (the approximation to the closed set attack proposed by Yu et al). Using these implementations, we evaluate the empirical performance of these methods on the Monero dataset in two ways - firstly using data only from the main Monero chain and secondly using data from four hard forks of Monero in addition to the main Monero chain. We have released the scripts used to perform the empirical analysis along with step-by-step instructions.

Subject Classification

ACM Subject Classification
  • Security and privacy → Distributed systems security
  • Cryptocurrency
  • CryptoNote
  • Monero
  • Traceability


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