Explore a groundbreaking framework for generating hybrid Multi-Party Computation (MPC) protocols in this 15-minute IEEE conference talk. Delve into the innovative Silph framework, designed to enhance scalability and accuracy in MPC protocol generation. Learn from experts Edward Chen, Jinhao Zhu, Alex Ozdemir, Riad Wahby, Fraser Brown, and Wenting Zheng as they present their collaborative research from Carnegie Mellon University and Stanford University. Gain insights into how Silph addresses challenges in MPC protocol development and its potential impact on secure multi-party computations across various applications.
Silph - A Framework for Scalable and Accurate Generation of Hybrid MPC Protocols
Overview
Syllabus
Silph: A Framework for Scalable and Accurate Generation of Hybrid MPC Protocols
Taught by
IEEE Symposium on Security and Privacy
Tags
Related Courses
-
SPDZ2k - Efficient MPC mod 2^k for Dishonest Majority
-
ADI - Adversarial Dominating Inputs in Vertical Federated Learning Systems
-
The Round Complexity of Perfect MPC with Active Security and Optimal Resiliency
-
Going Beyond Dual Execution - MPC for Functions with Efficient Verification
-
Scalable Multi-Party Computation Protocols for Machine Learning in the Honest-Majority Setting
-
Constant Round MPC with Fairness and Guarantee of Output Delivery
