SaTC: CORE: Small: New Approaches to Decentralized Differential Privacy

最近，谷歌和苹果部署了大型系统，用于对分散的用户数据进行不同的私人收集和分析。这些系统使用本地隐私模式，其中不收集敏感用户数据。这种本地模型具有许多实现优势，但不能捕获最具表现力的私有算法。这些更具表现力的私有算法本质上需要一个隐私的中央模型，在该模型中，受信任方同意收集敏感数据，并仅透露某些私有算法的结果。在许多应用程序中，找到受信任的聚合器可能会有问题。该项目通过使用密码学来设计和实现可扩展的安全协议来对分散的用户数据进行统计分析，该协议结合了中央和本地隐私模型的最佳特征。本项目引入并研究了一种新的基于匿名计算的分散隐私中间模型。此模型中的协议与本地隐私模型中的协议一样简单，但绕过了本地模型中协议的一些限制。对于在此中间模型中无法实现的功能，该项目设计了量身定制的安全密码，以在没有可信数据收集器的情况下实现这些功能，同时克服了通用协议的高通信、计算和循环复杂性开销。调查人员将让研究生和本科生参与这项研究。这一奖项反映了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。

Recently, Google and Apple have deployed large systems for differentially private collection and analysis of decentralized user data. These systems use a local model of privacy in which no sensitive user data is collected. This local model enjoys many implementation advantages, but does not capture the most expressive private algorithms. These more expressive private algorithms inherently require a central model of privacy, in which a trusted party agrees to collect the sensitive data and reveal only the outcome of some private algorithm. Finding a trusted aggregator can be problematic in many applications. This project specifically addresses this tension by using cryptography to design and implement scalable secure protocols for the statistical analysis of decentralized user data that combine the best features of the central and local models of privacy.This project introduces and studies a novel intermediate model for decentralized privacy based on anonymous computation. Protocols in this model enjoy the same simplicity as protocols in the local model of privacy, but bypass some of the limitations of protocols in the local model. For functionalities that cannot be achieved in this intermediate model, this project designs tailored secure cryptographic to implement these functionalities without a trusted data collector, while overcoming the high communication, computation, and round complexity overheads of generic protocols. The investigators will involve graduate and undergraduate students in this research.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.