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

EAGER：协作：云计算的整体安全性：不经意的计算

• 批准号: 1347279
• 负责人: Srini Devadas
• 金额: $ 10万
• 依托单位: Massachusetts Institute of Technology
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-09-01 至 2017-02-28
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1347279&HistoricalAwards=false
• 关键词: EAGER; Collaborative; Holistic; Security; Cloud

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.

更广泛地采用云存储和计算服务的主要障碍之一是需要保持数据隐私。最近，一些研究团体已经开始探索新的技术，允许客户端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。这些技术根据大量因素而变化很大，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成部分的信任程度。这个高度合作的项目结合了许多不同领域的专业知识，其目的是从根本上改变外包数据和计算在真实的世界中被感知和使用的方式。该项目的重点是找到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，该空间结合了算法技术、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，允许人们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。该项目还将探讨这些解决方案中的每一个可以实现的理论和实践限制，并磨练出一个可行的解决方案，该解决方案可能结合了许多不同的技术，以实现效率和安全性的正确平衡。