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.

更广泛采用云存储和计算服务的主要障碍之一是需要保持数据私密。最近，一些研究社区已经开始探索新技术，这些新技术使客户可以将存储和计算外将私人数据的存储和计算外包给潜在的不受信任的云服务，同时保持数据的隐私。这些技术高度不同，具体取决于大量因素，例如输入和输出数据的所有权，所需的处理类型，所需的保护水平以及客户愿意放入外包服务的不同组件的信任水平。这个高度协作的项目将许多不同的专业知识结合在一起，以实质性地改变了现实世界中的外包数据和计算的方式。该项目着重于在外包计算的背景下找到一种模块化方法，以确定隐私保存机制的规范，设计和分析。研究人员探索了一个宽阔的解决方案空间，该空间结合了算法技术，有限的信任硬件使用以及分布式计算和信任，并创建一个通用框架，该框架允许人们以模块化和合成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每种解决方案中每种解决方案中每种解决方案中的实用解决方案的实用解决方案的理论和实际限制，该解决方案可能结合了许多不同的技术，以实现效率和安全的正确平衡。