Standardizing On-Chain Tracing: From 'Address Clustering' to Systematic Decomposition
Blockchain analytics firm Chainalysis has released a methodology proposal aimed at establishing a unified on-chain fund tracing standard for law enforcement agencies and investigators. The core of the proposal is to systematically decompose the currently non-standardized concept of 'address clustering'—identifying groups of addresses and inferring their likely control relationships. Chainalysis defines the on-chain analysis structure in the form of an ontology, breaking clustering into wallet segments and functional roles.
The framework describes on-chain relationships through a two-layer structure: the first layer defines the transaction graph topology, i.e., the flow paths and node relationships of funds; the second layer evaluates inference confidence, i.e., the reliability of address aggregation based on the chain of evidence. Chainalysis states that this design aims to improve the interpretability and legal applicability of on-chain forensic methods, allowing courts and investigators to better understand how analytical conclusions are derived.
Practical Validation and Open Industry Discussion
The proposal is not purely theoretical; it has been designed and validated based on Chainalysis' practical experience in U.S. Department of Justice cases. A notable example is the application of on-chain fund flow analysis in the Bitcoin Fog mixer case. According to Chainalysis Chief Scientist Jacob Illum, the core goal of the proposal is to answer a key question: 'On what evidentiary basis can we conclude that these addresses belong to the same entity?' However, he stressed that on-chain analysis alone cannot directly identify the real-world identities of end users; it must be combined with legal investigative methods from centralized entities such as exchanges to complete identity attribution.
Chainalysis has opened the standard proposal for industry discussion, aiming to drive on-chain analysis methods toward more uniform technical specifications in law enforcement and compliance. Currently, different blockchain analytics tools vary significantly in address aggregation algorithms and confidence assessments. A unified ontology standard could enhance cross-platform and cross-case analytical consistency.