CAREER: Privacy-Preserving Sharing of Genomic Databases

在降低DNA测序成本方面取得了实质性进展，从而产生和获得了大量基因组数据。公开这些数据并在各机构之间共享基因组数据库，对于为个性化医疗铺平道路至关重要。然而，共享基因组数据有很大的风险，这些数据携带着许多关于所有者的敏感信息，例如他/她的疾病倾向(例如，阿尔茨海默氏症)、血统和身体特征。一个人的基因组与他/她的家庭成员的基因组相关，从而导致相互依赖的隐私风险，这一事实放大了对基因组隐私的威胁。在这个项目中，主要的研究目标是开发隐私保护技术，用于在不同的环境下共享基因组数据库(以及关于基因组数据库的统计数据)，这些环境包括：(I)当数据库所有者(研究人员)共享关于其数据库的统计数据时；(Ii)当数据库所有者与客户共享其整个数据库时(例如，在数据使用协议之后)；以及(Iii)当数据库所有者将其数据库的存储和处理外包给第三方云服务器时。该项目还将解决重要和具有挑战性的问题，例如客户对共享统计数据的核查、共享数据库未经授权共享时的责任以及最大限度地利用共享数据。对于所有开发的技术，项目团队将使用最先进的基因组隐私量化算法来评估/量化隐私。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

Substantial progress has been achieved towards reducing the cost of DNA sequencing, resulting in generation and availability of large amounts of genomic data. Public availability of this data and sharing of genomic databases between institutions are vital to paving the way towards personalized medicine. However, there are significant risks in sharing genomic data, which carries a lot of sensitive information about its owner, such as his/her disease predispositions (e.g., for Alzheimer's), ancestry, and physical attributes. This threat to genomic privacy is magnified by the fact that a person's genome is correlated to his/her family members' genomes, thus leading to interdependent privacy risks. In this project, the main research objective is to develop privacy-preserving techniques for sharing genomic databases (and statistics about genomic databases) under diverse settings that include the following: (i) when a database owner (researcher) shares statistics about its database; (ii) when a database owner shares its entire database (e.g., after data use agreements) with a client; and (iii) when database owners outsource the storage and processing of their databases to a third-party cloud server. The project will also address important and challenging issues, such as, verification of shared statistics by a client, liability of shared databases in case of their unauthorized sharing, and maximizing the utility of shared data. For all developed techniques, the project team will evaluate/quantify privacy using state-of-the-art genomic privacy quantification algorithms.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.