Sharpening Ponzi Schemes Detection on Ethereum with Machine Learning

Letterio Galletta, Fabio Pinelli

Abstract: Blockchain technology has been successfully exploited for deploying new economic applications. However, it has started arousing the interest of malicious users who deliver scams to deceive honest users and to gain economic advantages. Among the various scams, Ponzi schemes are one of the most common. Here, we present an automatic technique for detecting smart Ponzi contracts on Ethereum. We release a reusable data set with 4422 unique real-world smart contracts. Then, we introduce a new set of features that allow us to improve the classification. Finally, we identify a small and effective set of features that ensures a good classification quality.