Current Research

A novel fund distribution structure we identified and formalized through analysis of state-sponsored cryptocurrency laundering. The pattern operates through recursive splitting where, from N transaction outputs at each generation, one proceeds to off-ramp services while N-1 continue splitting — creating exponentially growing transaction trees.

Analysis ongoing across 6,630-transaction dataset. Paper in progress.

The Common Input Ownership Heuristic is foundational to blockchain forensics, yet published error rates range from 10% to over 90% across studies. We're documenting the scientific validation gaps that challenge court admissibility and working toward standardized benchmarks meeting Daubert evidentiary standards.

Literature review complete. Methodology development in progress.

Temporal patterns in Bitcoin transactions — from network-level propagation to behavioral signatures — remain underexplored. We've mapped the research landscape, identifying that network-level techniques achieve 11-60% deanonymization while behavioral analysis enables entity classification with 50-90% accuracy.

Literature review complete. Research design phase.