Paper 2026/1933

Provenance Graphs for AML/CFT: Asset Tracing and Freezing in Private Payments

Abstract

Anti-money laundering and counter-terrorist financing (AML/CFT) rules require payment service providers to assess incoming funds' provenance: for a target account, which earlier transfers contributed to it, how closely, and through which intermediaries? On transparent ledgers such as Bitcoin or Ethereum, this reduces to a graph traversal over the public transaction history. In private payment systems such as Zerocash or Tornado Cash Nova coins are burnt and created at each payment, while the sender, receiver, and amount are hidden. Provenance analysis is then impossible: the cryptography protects ordinary and illicit users alike. This creates an apparent deadlock, not merely a trade-off. We avoid this deadlock by giving a regulator a specific and bounded investigative capability rather than full visibility or none. Our construction extends Zerocash but applies naturally to most private systems with the same spend-and-create coin model (Tornado Cash, Railgun, Lelantus, etc.) The capability is backward provenance within a bounded neighbourhood of a transfer, together with the power to freeze funds derived from a designated illicit source, and to reconstruct a full clear-text provenance graph when a holder chooses to disclose. Everything outside that capability remains hidden from the supervisor and from every other party: receivers, amounts, the link from an output to its later spend, and the provenance of any coin that has not been disclosed.