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: 1664445
• 负责人: Abhi Shelat
• 金额: $ 25万
• 依托单位: Northeastern University
• 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 2019-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1664445&HistoricalAwards=false
• 关键词: TWC; Small; Collaborative; Iterative; Approach

Secure multi-party computation (MPC) 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 Principal Investigator's prior work for constructing special-purpose secure MPC protocols for greedy algorithms, this project develops new techniques that exploit the algorithmic structure of a function in order to develop more efficient secure computation protocols. The project develops new methods to achieve security against covert adversaries for linear algebraic tasks, graph matching algorithms, and problems from computational geometry. 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.

安全的多方计算（MPC）允许几个相互不信任的政党执行联合计算，同时保持其私人投入。该项目开发了用于构建具有低通信开销的两党安全计算协议的新技术。 在主要研究者的先前工作的基础上，该项目为贪婪算法构建特殊的安全MPC协议，开发了新技术，这些技术利用了功能的算法结构，以开发更有效的安全计算协议。该项目开发了针对线性代数任务，图形匹配算法以及计算几何问题的秘密对手的新方法。研究人员广泛传播了研究和软件库的结果，以使理论家和从业者受益。该项目包括各种教育和推广活动，例如为高中生组织研讨会。该项目为与这些构造相关的加密结构和安全概念创建了Wiki。