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Title: Ethereum Hidden Dangers: Ponzi Scheme Detection in Smart Contracts Using SourceP
Authors: Noor Ul Ain Afzal, Muhammad Kamran Abid, Muhammad Fuzail, Naeem Aslam, Nasir Umer
Journal: Kashf Journal of Multidisciplinary Research (KJMR)
| Category | From | To |
|---|---|---|
| Y | 2024-10-01 | 2025-12-31 |
Publisher: Kashf Institute of Development & Studies
Country: Pakistan
Year: 2025
Volume: 2
Issue: 4
Language: en
DOI: 10.71146/kjmr390
Keywords: source code analysisEthereum BlockchainSmart Ponzi SchemesIntelligent Contract Detection
Ponzi schemes have surfaced on the Ethereum platform as blockchain technology continues to gain traction. Using smart contracts, these schemes, also referred to as smart Ponzi schemes, have caused significant financial losses and adverse effects. Byte code features, op code characteristics, account qualities, and smart contract transaction behavior are the main focus areas for current Ethereum smart Ponzi scheme detection techniques. However, these methods often do not record the behavioral features of the Ponzi scheme, resulting in high false alarm rates and poor identification accuracy. In this study, we provide the source P. Source P is a unique way of knowing intelligent Ponzi schemes on the Ethereum platform, passed by dataflow. Using the intelligent contract's source code as a function eliminates the difficulty of collecting data and extracting functions from available identification methods. In particular, we convert the code into statistical flow diagrams, apply educated models, and use code representations to create classification models for the detection of Ponzi schemes. Experimental results show that SourceP outperforms cutting-edge technology in terms of sustainability and effectiveness, achieving an F1 score of 92.4% and a recall of 90.1% in Ethereum's smart Ponzi schema detection. Ponzi, Blockchain, Source Code, Intelligent Contracts.
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