ITR - (ASE+NHS) - (dmc+int): Privacy-Preserving Data Integration and Sharing

ITR - (ASE NHS) - (dmc int):隐私保护数据集成和共享

基本信息

  • 批准号:
    0428168
  • 负责人:
  • 金额:
    $ 100万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
    Standard Grant
  • 财政年份:
    2004
  • 资助国家:
    美国
  • 起止时间:
    2004-09-15 至 2008-08-31
  • 项目状态:
    已结题

项目摘要

Integrating and sharing data from multiple sources has been a long-standing challenge in the database community. This problem is crucial in numerous contexts, including data integration for enterprises and organizations, data sharing on the Internet, collaboration among government agencies, and the exchange of scientific data. Many applications of national importance, such as emergency preparedness and response; as well as research in many scientific domains, require integrating and sharing data among participants.Data integration is seriously hampered by an inability to ensure privacy. Without a privacy framework, sources are reluctant to share their data. Problems include fear of disclosing confidential information as well as regulations protecting individual privacy. While there has been progress in computing aggregations of distributed data without disclosing that data; e.g., privacy-preserving distributed data mining, it assumes data integration problems (schema matching, record linkage) are solved. As a consequence, the lack of a privacy-preserving data integration framework has become a key bottleneck to deploying data integration.This project will develop the technology needed to create and manage federated databases while controlling the disclosure of private data. While the emphasis will be on general techniques for data integration that preserve privacy, the project will work in the context of diverse but particularly relevant problem domains, including scientific research and emergency preparedness. Involvement of domain experts from these fields in developing and testing the techniques will ensure impact on areas of national importance.
集成和共享来自多个来源的数据一直是数据库社区的一个长期挑战。 这个问题在许多情况下都是至关重要的,包括企业和组织的数据集成、互联网上的数据共享、政府机构之间的协作以及科学数据的交换。 许多具有国家重要性的应用,如应急准备和反应,以及许多科学领域的研究,都需要在参与者之间整合和共享数据,数据整合因无法确保隐私而受到严重阻碍。 如果没有隐私框架,信息来源就不愿意分享他们的数据。 问题包括担心泄露机密信息以及保护个人隐私的法规。 虽然在计算分布式数据的聚合而不公开该数据方面已经取得了进展;例如,隐私保护分布式数据挖掘,它假设数据集成问题(模式匹配,记录链接)得到解决。 因此,缺乏保护隐私的数据集成框架已成为部署数据集成的关键瓶颈。本项目将开发创建和管理联邦数据库所需的技术,同时控制私有数据的泄露。 虽然重点将放在保护隐私的数据整合的一般技术上,但该项目将在各种不同但特别相关的问题领域,包括科学研究和应急准备方面开展工作。 这些领域的专家参与开发和测试技术将确保对国家重要领域的影响。

项目成果

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Christopher Clifton其他文献

Christopher Clifton的其他文献

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{{ truncateString('Christopher Clifton', 18)}}的其他基金

Collaborative Research: SaTC: CORE: Medium: Broad-Spectrum Facial Image Protection with Provable Privacy Guarantees
合作研究:SaTC:核心:中:具有可证明隐私保证的广谱面部图像保护
  • 批准号:
    2114123
  • 财政年份:
    2021
  • 资助金额:
    $ 100万
  • 项目类别:
    Standard Grant
Collaborative Research: Workshop to Develop a Roadmap for Greater Public Use of Privacy-Sensitive Government Data
合作研究:制定路线图以扩大公众使用隐私敏感政府数据的研讨会
  • 批准号:
    2129895
  • 财政年份:
    2021
  • 资助金额:
    $ 100万
  • 项目类别:
    Standard Grant
FAI: Identifying, Measuring, and Mitigating Fairness Issues in AI
FAI:识别、衡量和缓解人工智能中的公平问题
  • 批准号:
    1939728
  • 财政年份:
    2020
  • 资助金额:
    $ 100万
  • 项目类别:
    Standard Grant
Collaborative Research: ITR: Distributed Data Mining to Protect Information Privacy
合作研究:ITR:分布式数据挖掘保护信息隐私
  • 批准号:
    0312357
  • 财政年份:
    2003
  • 资助金额:
    $ 100万
  • 项目类别:
    Standard Grant
Shared Software Database
共享软件数据库
  • 批准号:
    9210704
  • 财政年份:
    1992
  • 资助金额:
    $ 100万
  • 项目类别:
    Continuing Grant

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