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

安全多方计算（MPC）允许互不信任的各方对其私有数据进行安全计算。该项目的目标是提供新颖的MPC解决方案，这些解决方案既高效，又支持在各自的本机表示下对输入进行不同复杂性的操作。在效率目标的驱动下，本项目研究了离线-在线模式下的MPC协议设计理论。该项目的成果有可能产生实用且可扩展的MPC协议，这些协议可以在隐私保护数据挖掘、机制设计和分布式线性代数计算等不同领域找到应用。本项目定义了计算相关性理论，利用安全保证对计算硬度结果进行论证，并在实际明显传输协议的设计和分析中引入了计算通道的概念。这个理论可以使成熟的信息论技术的工具箱转移到计算有界的设置。培训下一代密码学研究和安全专业人员是该项目的中心目标。这些倡议包括为本科和研究生课程设计和开发新课程和课程材料，以及让少数民族和妇女学生参与研究。该项目还为传播知识编写了积极的学习材料。

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.