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

安全多方计算(MPC)允许相互不信任的各方安全地计算他们的私有数据。这个项目的目标是提供新的MPC解决方案，这些解决方案是高效的，并且同时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-在线范式下的MPC协议设计理论。该项目的成果有可能产生实用和可扩展的MPC协议，这些协议在隐私保护数据挖掘、机制设计和分布式线性代数计算等领域都有应用。该项目定义了计算相关性理论，利用安全保证来论证计算难度结果，并在实用的明显传输协议的设计和分析中引入了计算通道的概念。这一理论可以将成熟的信息论技术工具包转移到计算受限的环境中。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。这些举措包括为本科生和研究生课程设计和开发新的课程和课程材料，以及让少数群体和女性学生参与研究。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.