Kernkonzepte
Blockchain technology has enabled new economic applications, but also attracted malicious actors deploying Ponzi schemes to deceive users. This paper presents an explainable machine learning approach to effectively detect smart Ponzi contracts on the Ethereum blockchain.
Zusammenfassung
The paper addresses the problem of detecting Ponzi schemes on the Ethereum blockchain, which have become a common scam targeting cryptocurrency users. The authors make the following key contributions:
They release a reusable dataset of 4,422 real-world Ethereum smart contracts, with 3,749 labeled as non-Ponzi and 673 as Ponzi schemes.
They develop a binary classification model using the Light Gradient Boosting Machine (LGBM) algorithm that outperforms previous approaches in terms of the Area Under the Curve (AUC) metric.
The authors introduce a set of new features to capture the characteristics of Ponzi schemes, such as the ratio of investment transactions to total transactions, the percentage of active days with transactions, and whether the contract initiator received Ether without investing.
Using explainable AI (XAI) techniques, the authors analyze the importance of the various features and identify a smaller set of 25 effective features that ensure good classification performance.
The analysis reveals that smart Ponzi contracts are characterized by a short lifetime, a small number of input transactions that provide high returns, and a small subset of investors being paid out, aligning with the known requirements of Ponzi schemes.
The comprehensive dataset, the improved classification model, and the insights into the key features that distinguish Ponzi schemes provide a valuable foundation for developing effective detection tools to protect cryptocurrency users from these fraudulent activities.
Statistiken
The number of unique real-world smart contracts in the dataset is 4,422.
The number of non-Ponzi contracts is 3,749 (84.78%).
The number of Ponzi contracts is 673 (15.22%).
Zitate
"Blockchain technology has been successfully exploited for deploying new economic applications. However, it has started arousing the interest of malicious actors who deliver scams to deceive honest users and to gain economic advantages."
"Ponzi schemes are one of the most common scams. Here, we present a classifier for detecting smart Ponzi contracts on Ethereum, which can be used as the backbone for developing detection tools."