Ethereum Phishing Scams Detection: A Survey

Abstract

The inherent anonymity of blockchain technology has made the cryptocurrency sector a breeding ground for a multitude of illicit financial crimes. In the realm of blockchain transaction security, phishing scams are widely considered a highly severe form of deceit, leading to significant economic losses. This paper provides an overview of past research findings on methods for detecting phishing scam in blockchain networks. Extending graph neural network approaches to detect phishing scam in blockchain networks will be of utmost importance. Graph neural networks yield models with superior generalization capabilities in comparison to conventional approaches. Future research will involve examining high-quality datasets and evaluating the influence of transaction graphs and transaction subgraphs on the effectiveness of detecting phishing scam nodes in categorization. The primary objective is to construct a more resilient model that can achieve the desired detection outcomes and differentiate phishing scams nodes with greater efficiency and precision.