Design of Financial Anti-fraud Application System Driven by Blockchain and Federated Learning

Yizhuo Quan; Chenlu Hu

doi:10.47297/wspdecWSP2515-797320.20250906

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Design of Financial Anti-fraud Application System Driven by Blockchain and Federated Learning

9卷第6期

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Design of Financial Anti-fraud Application System Driven by Blockchain and Federated Learning
Design of Financial Anti-fraud Application System Driven by Blockchain and Federated Learning
School of Information Engineering, Xi'an Mingde Institute of Technology, Xi'an, Shaanxi, 7101244, China
2025年9卷第6期页码：108-111
纸质出版日期：2025-06-30
DOI：10.47297/wspdecWSP2515-797320.20250906
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(2025). Design of Financial Anti-fraud Application System Driven by Blockchain and Federated Learning. 发展经济学, 9(6), 108-111.

Quan Yizhuo,Hu Chenlu.Design of Financial Anti-fraud Application System Driven by Blockchain and Federated Learning[J].Development Economics of China,2025,09(06):108-111.
(2025). Design of Financial Anti-fraud Application System Driven by Blockchain and Federated Learning. 发展经济学, 9(6), 108-111. DOI： 10.47297/wspdecWSP2515-797320.20250906.

Quan Yizhuo,Hu Chenlu.Design of Financial Anti-fraud Application System Driven by Blockchain and Federated Learning[J].Development Economics of China,2025,09(06):108-111. DOI： 10.47297/wspdecWSP2515-797320.20250906.

摘要

Abstract

With the rapid development of financial technology

financial fraud methods are constantly evolving and upgrading

bringing severe challenges to the security and stability of the financial industry. Traditional anti-fraud methods are difficult to meet the current needs of financial risk prevention and control due to problems such as data silos and privacy protection. To this end

this paper proposes and designs a financial anti-fraud application system architecture that integrates blockchain and federated learning technology. Through federated learning

the system realizes joint modeling of multiple institutions without sharing original data

thereby improving the accuracy and robustness of fraud detection models; at the same time

combined with the tamper-proof and traceable characteristics of blockchain

it ensures the transparency and credibility of model training and parameter interaction processes

further enhancing the security and compliance of the system. This paper analyzes the functional architecture and key technical implementation of the system in detail

including model construction

privacy protection mechanism

smart contract design

etc.

designs specific interaction processes

and conducts prototype development and experimental verification. The experimental results show that the proposed system can effectively improve the accuracy and real-time response capabilities of financial fraud detection while ensuring data privacy and security. This study provides new ideas and practical references for the development of financial anti-fraud technology under the background of multi-institutional collaboration.

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Keywords

references

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