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