The applications we use every day deal with privacy-sensitive data that come from different sources and entities, hence creating a tension between more functionality and privacy. Secure Multiparty Computation (MPC), a fundamental problem in cryptography and distributed computing, tries to resolve this tension. But despite classic feasibility results, the practice of secure computation lags behind its theory by a wide margin.
This talk will discuss my recent research effort to make secure computation practical. I will focus on a particularly promising approach, namely server-aided MPC. This approach allows one to tap the resources of an *untrusted cloud service* to design more efficient and scalable privacy-preserving protocols. I will discuss several variants of the server-aided model, our general- and special-purpose constructions for these variants, and the experimental results obtained from our implementations.