/explore
|
You are here |
blog.openmined.org | ||
| | | | |
jeremykun.com
In this article I'll derive a trick used in FHE called sample extraction. In brief, it allows one to partially convert a ciphertext in the Ring Learning With Errors (RLWE) scheme to the Learning With Errors (LWE) scheme. Here are some other articles I've written about other FHE building blocks, though they are not prerequisites... |
|
| | | | | ||
| | | | |
www.ayoub-benaissa.com
This is the first of a series of blog posts about the use of homomorphic encryption for deep learning. Here I introduce the basics and terminology as well as link to external resources that might help with a deeper understanding of the topic. |
|
| | | | | ||
| | | | |
windowsontheory.org
Guest post by Boaz Barak and Zvika Brakerski (part 2) In the previous post, we demonstrated the versatility of fully homomorphic encryption and its applicability for multiple applications. In this post we will demonstrate (not too painfully, we hope) how fully homomorphic encryption is constructed. Our goal is to present the simplest solution that (we... |
|
| | | | | ||
| | | | |
jeremykun.wordpress.com
The Learning With Errors problem is the basis of a few cryptosystems, and a foundation for many fully homomorphic encryption (FHE) schemes. In this article I'll describe a technique used in some of these schemes called modulus switching. In brief, an LWE sample is a vector of values in $\mathbb{Z}/q\mathbb{Z}$ for some $q$, and in... |
|
| | | |||