SaTC: CORE: Medium: Collaborative: Rethinking Access Pattern Privacy: From Theory to Practice

当程序访问存储在内存、磁盘或远程服务器上的数据时，其访问模式可能会泄露有关秘密输入和数据的信息。几十年来，人们一直在研究如何使程序“无关”，这样它的访问模式就不会泄露任何关于秘密输入或数据的信息。然而，过去的技术会产生相当大的性能开销。该项目构思和研究了访问模式隐私的新的、宽松的概念，并发现了以很少甚至没有开销实现这种隐私概念的新算法。该项目包括培养博士生和博士后研究人员，以及针对高中生、本科生和研究生的指导活动。这个项目重新思考了访问模式隐私的定义，包括（但不限于）一个称为“差异遗忘”的新概念，它是访问模式的差异隐私类比。该项目建立了对各种隐私概念影响程序性能的程度的理论理解，包括新的下限和上限。研究人员还探讨了新的隐私保护算法在云外包和数据库场景中的实际性能。该项目为新的差分无关算法和数据结构开发了开源库。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

When a program accesses data stored in memory, disk, or on a remote server, its access patterns can leak information about the secret inputs and data. There has been decades of work that investigated how to make a program "oblivious", such that its access patterns leak nothing about the secret inputs or data. Past techniques, however, incur a considerable performance overhead. This project conceives and investigates new, relaxed notions of access pattern privacy, and discovers new algorithms that achieve such notions of privacy with little to no overhead. The project includes training of Ph.D. students and postdoctoral researchers, and mentoring activities focused on high school, undergraduate, and graduate students.This project rethinks the definition of access pattern privacy, including (but not limited to) a new notion called "differential obliviousness" that is the differential privacy analog for access patterns. The project establishes theoretical understanding, including new lower and upper bounds, of the extent to which various privacy notions impact the performance of programs. The investigators also explore the practical performance of new privacy-preserving algorithms in cloud outsourcing and database scenarios. The project develops open-source libraries for the new, differentially oblivious algorithms and data structures.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.