TWC: Small: Collaborative: An Iterative Approach to Secure Computation

TWC：小型：协作：安全计算的迭代方法

• 批准号: 1618884
• 负责人: Muthuramakrishn Venkitasubramaniam
• 金额: $ 24.95万
• 依托单位: University of Rochester
• 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: 2016-09-15 至 2021-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1618884&HistoricalAwards=false
• 关键词: TWC; Small; Collaborative; Iterative; Approach

Secure multi-party computation (SMC) allows several mutually untrusting parties to perform joint computations while keeping their inputs private. This project develops new techniques for constructing two-party secure computation protocols with low communication overhead. Building on the PIs prior work for constructing special-purpose secure computation protocols for greedy algorithms, this project aims to develop new techniques that exploit the algorithmic structure of a function in order to develop more efficient secure computation protocols. Of particular interest in this project are linear algebraic tasks, graph matching algorithms, and problems from computational geometry. The project develops new methods to achieve security against covert adversaries for these problems.The investigators broadly disseminate the outcomes of the research and software libraries in order to benefit both theoreticians and practitioners. The project includes various educational and outreach activities such as organizing workshops for high-school students. The project has created a wiki for cryptographic constructions and security notions associated with these constructions.

安全多方计算（SMC）允许几个相互不信任的各方执行联合计算，同时保持他们的输入私有。本计画将发展新的技术，以建构具有低通讯负担的两方安全计算协定。 基于PI先前为贪婪算法构建专用安全计算协议的工作，该项目旨在开发利用函数的算法结构的新技术，以开发更有效的安全计算协议。 在这个项目中特别感兴趣的是线性代数任务，图匹配算法和计算几何问题。该项目开发了新的方法来实现对这些问题的隐蔽对手的安全性。调查人员广泛传播的研究和软件库的成果，以使理论家和实践者都受益。该项目包括各种教育和外联活动，如为高中学生举办讲习班。该项目创建了一个关于加密构造和与这些构造相关的安全概念的维基。