Explore a groundbreaking lecture on doubly efficient private information retrieval (DEPIR) and fully homomorphic encryption in the RAM model (RAM-FHE) presented by Daniel Wichs from Northeastern University. Delve into the innovative solution for creating a private variant of internet search, allowing users to query without revealing their searches to providers like Google. Discover how this research combines cryptographic tools with data structures for fast polynomial evaluation to construct the first schemes for DEPIR and RAM-FHE under standard cryptographic hardness assumptions, specifically Ring Learning with Errors. Learn about the potential applications of this technology in creating more secure and private online experiences, and understand how it improves upon previous heuristic candidate constructions. Gain insights into the collaborative work with Wei-Kai Lin and Ethan Mook, which addresses the challenge of efficiently processing encrypted search queries while maintaining user privacy.
Overview
Syllabus
Doubly Efficient Private Information Retrieval and Fully Homomorphic RAM Computation from Ring LWE
Taught by
Simons Institute