Overview
Learn about improved discrete Gaussian and subgaussian analysis techniques for lattice-based cryptography in this conference talk presented at PKC 2020. Explore a modular approach to discrete Gaussian analysis, covering lattice background, spherical and non-spherical discrete Gaussian sampling, smoothness properties, and applications to the Learning with Errors (LWE) problem. Gain insights into subgaussian random variables and matrices, addressing previous issues with unknown constants. Discover how these advancements contribute to the development of more efficient and secure lattice-based cryptographic systems.
Syllabus
Intro
Motivation: A Modular Approach to DG Analysis
Lattice Background
Spherical and Non-spherical DGS
Smoothness for Discrete Gaussians
Smoothness Continued
The Modular Approach
Smoothness in the Kernel Lattice
Adding Independent Samples BF11
Learning with Errors (LWE)
Generating LWE Samples
Subgaussian Random Variables
Subgaussian Random Matrices
Previous Problems: Unknown Constants
Solution: Everything Scales with o
Thank you!
Updated picture
Bibliography
Taught by
TheIACR