Privacy Preserving Crypto I: Secure Multi-Party Computation

This lecture covers Secure Multi-Party Computation (SMC) as a toolbox for privacy engineering, focusing on cryptographic techniques, Boolean and arithmetic circuits, and protocols like Yao's Garbled Circuits. It explains the security properties, threat models, and the ideal-world equivalent. The lecture also delves into the concept of honest but curious vs malicious parties, the use of additive secret shares, and Shamir's Secret Sharing. Real-world applications of SMC are discussed, such as the Estonian Study on graduation rates and data privacy in government agencies like the Tax Board and Ministry of Education, showcasing the benefits of MPC frameworks like Sharemind.