TWC: Small: General and Modular Secure Computation in the Offline-Online Paradigm

TWC：小型：离线-在线范式中的通用和模块化安全计算

• 批准号: 1618822
• 负责人: Hemanta Maji
• 金额: $ 50万
• 依托单位: Purdue 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: 2016-09-01 至 2021-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1618822&HistoricalAwards=false
• 关键词: TWC; Small; General; Modular; Secure

Secure multi-party computation (MPC) allows mutually distrusting parties to securely compute over their private data. The goal of this project is to provide novel MPC solutions that are efficient and simultaneously support operations of varying complexity on the input under their respective native representations. Driven by efficiency goals, this project studies the theory of MPC protocol design in the offline-online paradigm. The outcomes of this project have the potential to produce practical and scalable MPC protocols that find applications in diverse fields like privacy-preserving data mining, mechanism design and distributed linear algebra computations.This project defines the theory of computational correlations, leverages security guarantees to argue computational hardness results, and introduces the concept of computational channels in design and analysis of practical obvious transfer protocols. This theory could enable the transfer of the mature toolkit of information-theoretic techniques to the computationally bounded setting. Training the next generation of cryptography research and security professionals is a central goal of this project. The initiatives include design and development of new courses and course materials for undergraduate and graduate courses, and engagement of minority and women students in research. The project also develops active learning materials for the dissemination of knowledge.

安全的多方计算（MPC）允许互不信任的方可以安全地计算其私人数据。该项目的目的是提供新颖的MPC解决方案，这些解决方案有效且同时支持各自代表下的输入中不同复杂性的操作。在效率目标的驱动下，该项目研究了离线范式范式中MPC协议设计的理论。 The outcomes of this project have the potential to produce practical and scalable MPC protocols that find applications in diverse fields like privacy-preserving data mining, mechanism design and distributed linear algebra computations.This project defines the theory of computational correlations, leverages security guarantees to argue computational hardness results, and introduces the concept of computational channels in design and analysis of practical obvious transfer protocols.该理论可以使信息理论技术的成熟工具包转移到计算界设置。培训下一代密码学研究和安全专业人员是该项目的核心目标。这些举措包括针对本科和研究生课程的新课程和课程材料的设计和开发，以及少数民族和女学生参与研究。该项目还开发了积极的学习材料来传播知识。