网络与信息安全学报2024，Vol.10Issue(3)：156-174,19.DOI:10.11959/j.issn.2096-109x.2024047
生成式对抗网络在金融数据中的应用
Application of generative adversarial networks for financial data
摘要
Abstract
Data,recognized as a fundamental strategic resource and key production factor for a nation,has served as the foundational resource and innovation engine for economic and social development.The financial industry,characterized by its data-intensive and technology-driven nature,necessitates the optimal allocation of data assets to facilitate industrial upgrading.However,financial data commonly exhibits issues such as uneven distribution,in-formation asymmetry,and data silos,which have prevented data from fully realizing its value.To address these challenges,various generative models have been actively adopted by financial institutions to synthesize highly real-istic data,thereby breaking down data barriers and monopolies,and shaping the future trend of the financial indus-try.Among these models,Generative Adversarial Networks(GANs)have emerged as particularly popular,demon-strating impressive performance across various fields and showing great potential in generating financial tabular data,financial time series,and detecting financial fraud.The advantages of the GAN model compared with other generative models in the financial field were analyzed.The GAN models that have been applied to the financial field since Generative Adversarial Networks were proposed in 2014 were presented,and the principles of each model were introduced.The application practice of the GAN model in generating financial tabular data,generating financial time series,and financial fraud detection,as well as other financial data fields,was explored.Finally,the challenges and development direction of GANs for the future were discussed,taking into account the actual situa-tion in China.关键词
生成式对抗网络/金融科技/数据安全Key words
generative adversarial networks/fintech/data security分类
计算机与自动化引用本文复制引用
崔毅浩,刘森,叶广楠..生成式对抗网络在金融数据中的应用[J].网络与信息安全学报,2024,10(3):156-174,19.基金项目
中国工程院战略研究与咨询项目(2023-33-14) （2023-33-14）
上海市自然科学基金(23ZR1404900) （23ZR1404900）
国家重点研发计划项目(2023YFC3305200) （2023YFC3305200）
云南省重大科技专项计划(202402AD080005) Chinese Academy of Engineering Strategic Research and Consulting Project(2023-33-14),The Natural Sci-ence Foundation of Shanghai(23ZR1404900),National Key Research and Development Program of China(2023YFC3305200),Research on Key Technologies,Innovation and Application of Smart Port(202402AD080005) （202402AD080005）
