I-Corps: Trustworthy Synthetic Data Generation

I-Corps：值得信赖的综合数据生成

• 批准号: 2317549
• 负责人: Guang Cheng
• 金额: $ 5万
• 依托单位: University of California-Los Angeles
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-04-15 至 2025-03-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2317549&HistoricalAwards=false
• 关键词: Corps; Trustworthy; Synthetic; Data; Generation

The broader impact/commercial potential of this I-Corps project is to develop software products that support modern privacy enhancing technology. The project's core technology proposes data-rich applications for a new and trustworthy way to maintain data utility and protect data privacy. Using generative artificial intelligence (AI), the proposed technology unlocks greater data impact for small and medium sized businesses and organizations while aligning with modern privacy law. In addition, the software products have potential to target marginalized communities in "digital rights deserts," where clients and customers' digital rights are significantly limited by businesses and organizations capacity, data privacy awareness, and cost. With the proposed software products and accompanying auditing service, more individual businesses and companies may receive more access to their data benefits and care of their customers' digital rights regardless of their demographic and socio-economic background. This I-Corps project is based on the development of deep learning technology for tabular data synthesis. The project leverages the use of generative adversarial networks for trustworthy tabular data synthesis. The interdisciplinary academic-industrial collaboration experience provides a proven framework to integrate data synthesis technology into modern machine learning workflow to support and develop modern digital businesses and services. Pilot research was used to develop an integration of artificial intelligence algorithms towards audit quality and trustworthiness of synthesized tabular data to unlock safe, secure, cross sector data sharing. In addition, research has been performed with industrial partners in the social media platform sector to assess and polish the technology towards providing users privacy-preserving metrics and exercise evaluation through industrial-level machine learning pipelines. The proposed technology has the potential to positively change platform users' digital rights by significantly enhancing safety, security and anonymity, advancing digital law enforcement, and increasing data benefits for both digital service providers and users.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

该I-Corps项目的更广泛的影响/商业潜力是开发支持现代隐私增强技术的软件产品。该项目的核心技术为维护数据实用程序和保护数据隐私的新的且值得信赖的方法提出了丰富的应用程序。拟议的技术使用生成人工智能（AI），在与现代隐私法保持一致的同时，对中小型企业和组织的数据影响更大。此外，软件产品有可能针对“数字权利沙漠”中边缘化社区的目标，在这种情况下，客户和客户的数字权利受到企业和组织能力，数据隐私意识和成本的限制。借助拟议的软件产品和随附的审计服务，越来越多的个人企业和公司可能会获得更多的访问数据收益，并照顾客户的数字权利，而无论其人口统计和社会经济背景如何。这个I-Corps项目基于用于表格数据综合的深度学习技术的开发。该项目利用生成对抗网络的使用来可信赖的表格数据综合。跨学科的学术工业协作经验提供了一个验证的框架，可以将数据合成技术整合到现代机器学习工作流程中，以支持和开发现代的数字业务和服务。试点研究被用来开发人工智能算法的整合，以审核质量和合成表格数据的可信度，以解锁安全，安全，跨部门数据共享。此外，已经与社交媒体平台行业的工业合作伙伴进行了研究，以评估和修饰技术，以通过工业级的机器学习管道为用户提供隐私保护指标和锻炼评估。该提出的技术有可能通过显着提高安全性，安全性和匿名性，推进数字执法，并增加数字服务提供商和用户的数据益处，从而积极地改变平台用户的数字权利。该奖项反映了NSF的法定任务，并被认为是通过该基金会的知识分子功能和广泛影响来评估Criteria的评估，并被认为是值得的。