EAGER: Collaborative: Holistic Security for Cloud Computing: Oblivious Computation

广泛采用云存储和计算服务的主要障碍之一是需要保持数据的私密性。最近，几个研究团体已经开始探索新的技术，允许客户将私有数据的存储和计算外包给可能不受信任的云服务，同时保持数据的隐私。这些技术因多种因素而异，例如输入和输出数据的所有权、所需的处理类型、所需的保护级别以及客户愿意对外包服务的不同组件进行的信任级别。这个高度协作的项目结合了许多不同的专业领域，旨在显著改变外包数据和计算在现实世界中的感知和使用方式。该项目专注于寻找一种模块化的方法来规范、设计和分析外包计算环境中的隐私保护机制。研究人员探索了一个广泛的解决方案空间，其中结合了算法技术、受信任硬件的有限使用以及分布式计算和信任，并创建了一个通用框架，允许以模块化和可组合的方式比较和分析截然不同的解决方案。该项目还将探索每个解决方案所能实现的理论和实践限制，并研究可能结合许多不同技术以实现效率和安全性的正确平衡的实用解决方案。

One of the main impediment to a wider adoption of cloud storage and computing services is the need to keep data private. Recently, several research communities have begun exploring new techniques that allow a client to outsource storage and computation over private data to a potentially untrusted cloud service, while maintaining the privacy of the data. These techniques are highly varied depending on a large number of factors, like the ownership of the input and output data, the type of processing required, the desired level of protection, and the level of trust that the client is willing to put in different components of the outsourcing service. This highly collaborative project combines many different areas of expertise with the aim of substantially changing the way outsourced data and computation are perceived and used in the real world.This project focuses on finding a modular approach to the specification, design and analysis of privacy preserving mechanisms in the context of outsourced computation. The investigators explore a broad solution space that combines algorithmic techniques, limited use of trusted hardware, and distributed computation and trust, and create a common framework that allows one to compare and analyze vastly different solutions in a modular and composable manner. The project will also explore the theoretical and practical limits of what each of these solutions can achieve and hone in on a practical solution that possibly combines many different techniques to achieve the right balance of efficiency and security.