In the recent years, privacy has gone from a niche idea to a mainstream concern. From protecting against surveillance to data theft, to enabling new healthcare or financial applications, the need to securely process data has never been so important.
Fortunately, many techniques are becoming practical, from Fully Homomorphic Encryption (FHE) to Secure Multiparty Computation (SMPC) to Federated Learning and Differential Privacy. All solve the same underlying problem to computing without being able to see the actual data, thus protecting privacy by design.
In this meetup, we will go deep into these techniques, from the theory (math heavy!) to the implementations (engineering heavy!) to the usecases (not as heavy!).
Send a message to firstname.lastname@example.org if you'd like to present something