Collaborative Research: IMR: MM-1B: Foundations for Differentially Private Internet Measurement

合作研究：IMR：MM-1B：差分隐私互联网测量的基础

• 批准号: 2220434
• 负责人: Zhou Li
• 金额: $ 30万
• 依托单位: University of California-Irvine
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-10-01 至 2025-09-30
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2220434&HistoricalAwards=false
• 关键词: Collaborative; Research; IMR; MM; 1B

Internet measurement research has been providing critical insights and evidence support in guiding the design of Internet infrastructures. However, how to share and use Internet measurement data while respecting users' privacy is still challenging. To protect privacy, most works choose to anonymize sensitive fields or only publish the aggregated statistics, but such methods are vulnerable to privacy attacks. Differential privacy, which provides guaranteed privacy protection for data release, has gained prominent traction from companies and government agencies, and is a natural choice for sharing Internet measurement data. However, a critical gap remains to identify how differential privacy can be applied to networking problems. This project aims to understand privacy issues and then lay the foundations for deploying differential privacy in the processing pipeline of Internet measurement data. The project's broader significance and importance include transferring the technologies to industry, involving members from under-represented groups, and disseminating outcomes through K-12 outreach and community services.The project is structured around three main aims. Thrust 1 conducts a comprehensive study of the privacy issues in the existing practices in collecting and sharing Internet measurement data, and develops an inference attack benchmark to assess the privacy risks and the benefits of different protection mechanisms. Thrust 2 investigates how differential privacy can be adjusted and integrated into the processing pipeline of Internet measurement data, by developing new configurable and relaxed differential privacy notions. Thrust 3 develops methods to publish synthetic Internet measurement data while satisfying differential privacy.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.

互联网测量研究一直在为指导互联网基础设施的设计提供重要的见解和证据支持。然而，如何在尊重用户隐私的同时共享和使用互联网测量数据仍然具有挑战性。为了保护隐私，大多数作品选择对敏感字段进行匿名化或仅发布汇总统计数据，但此类方法容易受到隐私攻击。差异隐私为数据发布提供了有保障的隐私保护，受到了企业和政府机构的广泛关注，是共享互联网测量数据的自然选择。然而，在确定如何将差异隐私应用于网络问题方面仍然存在一个关键差距。该项目旨在了解隐私问题，然后为在互联网测量数据处理流程中部署差分隐私奠定基础。该项目更广泛的意义和重要性包括将技术转移到行业、让代表性不足群体的成员参与进来，以及通过 K-12 外展和社区服务传播成果。该项目围绕三个主要目标构建。 Thrust 1对现有收集和共享互联网测量数据实践中的隐私问题进行了全面研究，并开发了推理攻击基准来评估不同保护机制的隐私风险和收益。 Thrust 2 研究了如何通过开发新的可配置且宽松的差分隐私概念来调整差分隐私并将其集成到互联网测量数据的处理流程中。 Thrust 3 开发了在满足差异隐私的同时发布合成互联网测量数据的方法。该奖项反映了 NSF 的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。