A Proposed Algorithm for Detecting Mixers in Ethereum

• Pedro Leale UFU
• Ivan da Silva Sendin UFU

DOI: https://doi.org/10.5753/sbseg_estendido.2025.10916

Abstract

This work presents a methodology for detecting smart contracts of the mixer type on the Ethereum network. A machine learning model based on Random Forest was employed, trained with transactions from Tornado Cash and balanced with samples from 100 randomly selected addresses unrelated to mixers. The model was trained using data from March 2025 and validated on October 29, 2020—a day with high transaction volume—successfully identifying 3 Tornado Cash addresses.

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