Recycled or custodial wallets that reuse addresses create systematic address clustering errors because common heuristics treat multi-input transactions or repeated address usage as single ownership. These false merges distort attribution, undermine privacy assessments, and can mislead compliance or research outcomes. Sarah Meiklejohn University College London demonstrated early that standard heuristics can over-aggregate addresses, and Arvind Narayanan Princeton University emphasizes the limits of on-chain heuristics and the need for careful preprocessing to avoid misleading conclusions.
Heuristic-aware transaction filtering
A first line of preprocessing is to identify and exclude transactions that invalidate basic ownership assumptions. Flagging and removing known mixing patterns such as CoinJoin-style equal-value outputs, or transactions with many small inputs consolidating dust, prevents the multi-input heuristic from collapsing addresses that belong to distinct users. Applying temporal filters that restrict clustering to reasonable time windows around spending events reduces accidental links created by long-term consolidation activity.
Service-label and structural pruning
Because many recycled addresses originate from custodial services and exchanges, integrating public label sets and excluding addresses known to be shared prevents large, artificial clusters. Removing high-degree nodes and edges connected to addresses with repeated deposit reuse—typical of hosted wallets—limits the propagation of misattribution. Pruning the graph of known custodial infrastructure and treating their deposits as externalized flows instead of wallet-internal links keeps individual user wallets separate.
Additional preprocessing techniques include normalizing value units, collapsing dust outputs below a threshold to avoid spurious joins, and annotating transactions with provenance signals such as IP-derived tags or off-chain identifiers when ethically and legally available. Combining multiple evidence streams reduces reliance on any single heuristic.
The consequences of inadequate preprocessing are practical and ethical: investigators may wrongly accuse bystanders, researchers may overstate centralization, and privacy assessments can be invalid across jurisdictions where custodial behavior differs. Cultural and territorial nuances matter because reuse patterns vary by region and by service business model; exchanges in one jurisdiction may use per-user deposit addresses while others reuse a single pool. Mitigations therefore require continual updating of label sets, sensitivity to regional service practices, and transparent documentation of preprocessing choices to preserve reproducibility and to respect privacy and legal boundaries.