A Generative AI-Based Framework for Decentralized Finance and Cryptocurrency Fraud Prevention

Abstract

Although aligned with security-based principles, Blockchain networks have maintained some exposure to fraudulent transactions. This paper introduces a novel methodology and framework for effectively characterizing fraud within blockchain networks and a method for prevention. To leverage the transparency of the blockchain, suitable starting data can be acquired to characterize potentially nefarious transactions. The framework presented applies generative AI at two levels: to support the characterization of synthetic training data for scenarios that may yet be deployed and to generate suitable testing scenarios for constructing effective techniques to safeguard transactions.