In recent years, blockchain technology has introduced decentralized finance (DeFi) as an alternative to traditional financial systems. However, the growing popularity of DeFi has made it a target for fraudulent activities, resulting in significant losses. Researchers have explored the potential of artificial intelligence (AI) approaches to detect such fraudulent activities. This survey provides a systematic taxonomy of various frauds in the DeFi ecosystem, categorized by different stages of a project's life cycle. Various fraud types are identified, including Ponzi schemes, rug pulls, and fake token offerings. Detection methods include statistical modeling, natural language processing, and machine learning techniques. The study emphasizes the importance of early detection to prevent scams like honeypot contracts and exit scams.
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by Bingqiao Luo... at arxiv.org 03-14-2024
https://arxiv.org/pdf/2308.15992.pdfDeeper Inquiries