Chainalysis, a prominent blockchain analytics firm, published a proposed ontology for crypto analytics work on Monday, outlining standards it says can help investigators use high-quality data in tracing transactions across public ledgers.
Market Context
The proposal arrives as regulatory scrutiny of cryptocurrency transactions intensifies globally. Law enforcement agencies have increasingly relied on blockchain analytics tools to trace illicit funds, but the methodology behind these tools has often remained opaque to prosecutors and judges evaluating evidence.
The move also comes months after Chainalysis' Reactor software was tested in a U.S. courtroom setting. In the Department of Justice's case against Roman Sterlingov—the co-founder of crypto mixing service Bitcoin Fog convicted on money laundering charges in 2024—Judge Randolph Moss held what's known as a Daubert hearing to assess whether Chainalysis' analytical tools met evidentiary standards. The judge ultimately ruled that 'substantial evidence supports the government's submission that the software is highly reliable.'
Analysis
Chainalysis Chief Scientist Jacob Illum told CoinDesk that the proposal aims to establish industry standards for blockchain analytics, providing investigators and prosecutors with clearer benchmarks for evaluating forensic data.
'If I was the one who needed this information to actually either convict on or prosecute or investigate, what would I want a tool to do?' Illum said of his approach. 'What's supported by the data? That's my job—to tell an investigator as much as possible what you can do with what the data tells us.'
The ontology addresses one of blockchain analytics' persistent challenges: the concept of address "clusters." Current tools rely on clustering algorithms to identify which wallets might be under control of the same entity, but Illum noted that 'this term does not have a universal meaning across the industry.' The proposal breaks clusters into component parts—deposit addresses, change addresses, and other functional wallet types—to help investigators better assess what data they possess and how reliable it may be.
Chainalysis presents attribution through a two-tier framework. The first tier 'defines the structural graph,' while the second assesses confidence levels in that analytical construct. This distinction matters because investigators typically lack access to private keys, which would provide definitive proof of wallet control, forcing reliance on on-chain behavioral patterns instead.
Illum was clear about the methodology's limitations: While Chainalysis can trace funds to entities like exchanges or wallet service providers, it cannot independently identify actual end users without additional information such as subpoenas served on compliant platforms. 'Those two things really have nothing to do with each other,' he said, noting that cluster attribution and user identification are separate analytical questions requiring different evidence sources.
Key Numbers
- 2024: Year Roman Sterlingov was convicted in DOJ case where Chainalysis' Reactor software underwent Daubert evidentiary review
- $0: Cost to access public blockchain data, versus fees charged by analytics firms for attribution and clustering services
- 2: Number of tiers in Chainalysis' proposed ontology framework
What to Watch
Industry feedback on the proposed standards will be closely watched. Illum said the company expects response from crypto industry participants but has not yet actively solicited broad input beyond preliminary discussions with law enforcement groups.
The proposal's reception among defense attorneys and civil liberties advocates could shape future legal challenges to blockchain forensic evidence. If adopted more widely, such standards might provide defendants greater ability to challenge analytical methodologies in court.
Upcoming developments: Any formal responses from major crypto exchanges, compliance-focused industry groups, or law enforcement associations regarding the proposed ontology.