Systems and methods for entity labeling based on behavior

Abstract

Methods and systems use a second dataset comprising independently validated data based on labeled blockchain operations previously processed through the blockchain network. The use of the second dataset in conjunction with the dataset comprising labeled blockchain characteristics data received from a plurality of sources provides a comprehensive input for a machine learning model to identify and label suspicious blockchain operations. By doing so, the system mitigates fraudulent, criminal, or suspicious transactions. For example, the system may send an alert to a user if a behavior type is deemed a high risk by the machine learning model; the system may furthermore hold the funds associated with the blockchain operation in a separate account while the transaction is manually reviewed. Thus, the system may generate alerts to notify a user of a suspicious behavior type or suspicious blockchain operation, divert funds associated with the transaction, and conduct a manual review of suspicious blockchain operations.