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Technology of Blockchain
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App. Res. of Comp. Printed Article
Vol. 42, 2025 No. 2
357-364

Interpretable ICO fraud prediction model by fusing multi-source heterogeneous data

Lu Jiarong1
Liao Bin2
Liu Yi3
Chen Hailong1
1. College of Statistics & Data Science, Xinjiang University of Finance & Economics, rümqi 830012, China
2. College of Big Data Statistics, Guizhou University of Finance & Economics, Guiyang 550025, China
3. School of Public Health, Xinjiang Medical University, rümqi 830017, China
DOI: 10.19734/j.issn.1001-3695.2024.05.0220

Abstract

Aiming at the problems of single feature modelling and models lacking interpretability in the current ICO fraud detection research, this paper proposed an interpretable ICO fraud prediction model(IICOFP) by fusing multi-source heterogeneous data. Firstly, it fused the ICO project basic information, rating scores, social media and other multi-source heterogeneous data, and effectively achieved feature modelling of ICOs by Lasso feature selection and Tomek-Link under-sampling. Secondly, it trained the ICO fraud prediction model based on the GBDT algorithm, and introduced the SHAP framework to analyze the main influencing factors of fraudulent ICOs from multiple perspectives, which strongly enhanced the interpretability of the model. The experimental results show that the proposed IICOFP model achieves accuracy, precision, recall, F1 score and AUC value of 87.76%, 85.37%, 90.52%, 87.87% and 87.82%, respectively, and the performance of each of them is improved by about 2%~10% over the existing best model, which verifies the key role of fusing multi-source heterogeneous data for feature modelling in ICO fraud prediction(experimental data and code: https: //github. com/Lujiarong1203/IICOFP).

Foundation Support

新疆社会经济统计与大数据应用研究中心项目(XJEDU2024J100)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2024.05.0220
Publish at: Application Research of Computers Printed Article, Vol. 42, 2025 No. 2
Section: Technology of Blockchain
Pages: 357-364
Serial Number: 1001-3695(2025)02-005-0357-08

Publish History

[2025-02-05] Printed Article

Cite This Article

卢加荣, 廖彬, 刘怡, 等. 融合多源异构数据的ICO欺诈预测与可解释分析模型 [J]. 计算机应用研究, 2025, 42 (2): 357-364. (Lu Jiarong, Liao Bin, Liu Yi, et al. Interpretable ICO fraud prediction model by fusing multi-source heterogeneous data [J]. Application Research of Computers, 2025, 42 (2): 357-364. )

About the Journal

  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

Application Research of Computers has many high-level readers and authors, and its readers are mainly senior and middle-level researchers and engineers engaged in the field of computer science, as well as teachers and students majoring in computer science and related majors in colleges and universities. Over the years, the total citation frequency and Web download rate of Application Research of Computers have been ranked among the top of similar academic journals in this discipline, and the academic papers published are highly popular among the readers for their novelty, academics, foresight, orientation and practicality.

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