NetSE: Medium: Privacy-Preserving Information Network and Services for Healthcare Applications

NetSE：媒介：用于医疗保健应用程序的隐私保护信息网络和服务

• 批准号: 0905493
• 负责人: Ling Liu
• 金额: $ 107.63万
• 依托单位: Georgia Tech Research Corporation
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-09-15 至 2014-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0905493&HistoricalAwards=false
• 关键词: NetSE; Medium; Privacy; Preserving; Information

This research explores challenges in developing privacy-preserving information networks and services (PPNs). Next generation healthcare information systems and applications, such as personalized and predictive medicine, need PPNs for privacy-preserving information sharing and dissemination among independent healthcare providers, enabling information access over distributed access controlled content, while safeguarding personal health information and medical privacy of individuals from unauthorized disclosures.The intellectual merits of this research include the development of: (1) privacy-preserving search capabilities over distributed access controlled content, a critical functionality for PPNs; (2) a suite of utility-aware data anonymization services, preserving the privacy of personal medical information against unauthorized disclosure, at the same time maximizing the data utility for medical service providers; and (3) the PPN architecture and middleware optimized for high availability, scalability and failure recovery.The broad impact is two-fold. First, this research will create better and broader understanding of the challenges and functional requirements for building the next generation of privacy preserving networked information systems over distributed access controlled content. A domain-specific proof-of-concept prototype on top of the PPN core will be developed for discovering and analyzing risk factors for resistant bacterial infections. These real-world studies will be conducted in collaboration with Morehouse School of Medicine and Children's Healthcare of Atlanta, and be use as both a driver and a testbed for this research. Second, this research will demonstrate that the PPN is an enabling infrastructure for real-time, continuous and on demand data analysis over massively-distributed and privately-shared data repositories.

这项研究探讨了开发隐私保护信息网络和服务（PPN）方面面临的挑战。下一代医疗保健信息系统和应用程序，例如个性化和预测医学，需要 PPN 在独立医疗保健提供者之间共享和传播隐私保护信息，从而实现通过分布式访问控制内容进行信息访问，同时保护个人健康信息和个人医疗隐私免遭未经授权的披露。本研究的智力优点包括开发：（1）通过分布式访问控制的隐私保护搜索功能 内容，PPN 的一项关键功能； (2) 一套实用感知的数据匿名服务，保护个人医疗信息的隐私，防止未经授权的泄露，同时最大限度地提高医疗服务提供商的数据效用； (3) PPN 架构和中间件针对高可用性、可扩展性和故障恢复进行了优化。广泛的影响有两方面。首先，这项研究将更好、更广泛地理解在分布式访问控制内容上构建下一代隐私保护网络信息系统的挑战和功能要求。将开发 PPN 核心之上的特定领域概念验证原型，用于发现和分析耐药细菌感染的风险因素。这些现实世界的研究将与亚特兰大莫尔豪斯医学院和儿童保健学院合作进行，并将用作这项研究的驱动力和测试平台。其次，这项研究将证明 PPN 是一个支持基础设施，可以对大规模分布式和私人共享的数据存储库进行实时、连续和按需数据分析。