Heuristic Clustering

Heuristic clustering is a data analysis technique used in blockchain forensics to group multiple addresses that are likely controlled by the same entity. By applying specific rules and logical assumptions, analysts can infer that various addresses belong to a single wallet or user.

For example, if multiple inputs are used in a single transaction, it is highly probable that all those addresses are owned by the same person or entity. This method allows investigators to build a more comprehensive view of an entity's financial footprint across a public ledger.

It is a fundamental tool for mapping out the ownership structure of large holdings and identifying potential patterns of activity. While not always definitive, clustering provides a high degree of confidence when identifying clusters of addresses associated with exchanges, mixers, or known illicit actors.

It bridges the gap between raw, fragmented transaction data and actionable intelligence.