# Safeguarding the Evidential Value of Forensic Cryptocurrency Investigations

## TL;DR

This paper examines the legal and technical standards for cryptocurrency forensic analysis, especially focusing on clustering heuristics and attribution tags, to ensure the evidential value and compliance with legal standards.

## Contribution

It identifies legal requirements and proposes a data sharing framework to improve the reliability and legal standing of cryptocurrency forensic investigations.

## Key findings

- Analysis of CoinJoin transactions reveals potential misinterpretations in clustering heuristics.
- Proposed framework enhances legal compliance and evidential robustness in cryptocurrency forensics.
- Integration of framework can improve investigation effectiveness while safeguarding rights.

## Abstract

Analyzing cryptocurrency payment flows has become a key forensic method in law enforcement and is nowadays used to investigate a wide spectrum of criminal activities. However, despite its widespread adoption, the evidential value of obtained findings in court is still largely unclear. In this paper, we focus on the key ingredients of modern cryptocurrency analytics techniques, which are clustering heuristics and attribution tags. We identify internationally accepted standards and rules for substantiating suspicions and providing evidence in court and project them onto current cryptocurrency forensics practices. By providing an empirical analysis of CoinJoin transactions, we illustrate possible sources of misinterpretation in algorithmic clustering heuristics. Eventually, we derive a set of legal key requirements and translate them into a technical data sharing framework that fosters compliance with existing legal and technical standards in the realm of cryptocurrency forensics. Integrating the proposed framework in modern cryptocurrency analytics tools could allow more efficient and effective investigations, while safeguarding the evidential value of the analysis and the fundamental rights of affected persons.