TWC: Small: Techniques and Tools for General-Purpose Secure Computing and Outsourcing

TWC：小型：通用安全计算和外包的技术和工具

• 批准号: 1705262
• 负责人: Marina Blanton
• 金额: $ 10.85万
• 依托单位: SUNY at Buffalo
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-10-01 至 2017-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1705262&HistoricalAwards=false
• 关键词: TWC; Small; Techniques; Tools; General

The rapid advancement of techniques for secure computation on protected data offers a major incentive for development of tools for general-purpose secure computation that protects data privacy, as opposed to computation of specialized tasks. The recent emergence of cloud computing and the need to protect privacy of sensitive data used in outsourced computation serves as another major motivation for this work. With this in mind, this project targets at developing a compiler suitable for privacy-preserving execution of any functionality specified by a user program. Our compiler transforms a program written in an extension of the C programming language, where data to be protected are marked as private, into its secure distributed implementation in C, which can be consecutively compiled into a binary executable by a native compiler. The goal of the project is to preserve all features of the programming language and enable efficient implementation of user programs using a number of optimization techniques. The secure distributed computation is implemented using secure multi-party techniques on secret-shared data and is suitable for secure collaborative computation and secure computation outsourcing.These techniques will allow for more secure cloud computing, even in the presence of attackers. Other broader impacts include outreach to female middle school girls to increase interest in computer science, a summer school program for graduate students on secure computation in the cloud, and involving students from a nearby predominantly African-American university in the research program.

受保护数据的安全计算技术的快速发展为开发保护数据隐私的通用安全计算工具提供了主要激励，而不是专门任务的计算。最近出现的云计算和保护外包计算中使用的敏感数据隐私的需要是这项工作的另一个主要动机。考虑到这一点，这个项目的目标是开发一个编译器，适合于隐私保护执行用户程序指定的任何功能。我们的编译器转换的C编程语言，其中要保护的数据被标记为私有的扩展编写的程序，到其安全的分布式实现在C中，它可以连续编译成一个二进制可执行的本地编译器。该项目的目标是保留编程语言的所有功能，并使用一些优化技术有效地实现用户程序。安全分布式计算是在秘密共享数据上使用安全多方技术实现的，适用于安全协作计算和安全计算外包。这些技术将允许更安全的云计算，即使在存在攻击者的情况下。 其他更广泛的影响包括与女中学生的接触，以增加对计算机科学的兴趣，为研究生开设的关于云计算安全计算的暑期学校课程，以及让附近一所以非洲裔美国人为主的大学的学生参与研究计划。