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What is TFHE-rs?

TFHE-rs is a pure Rust implementation of TFHE for boolean and small integer arithmetics over encrypted data. It includes a Rust and C API, as well as a client-side WASM API.
TFHE-rs is meant for developers and researchers who want full control over what they can do with TFHE, while not having to worry about the low level implementation.
The goal is to have a stable, simple, high-performance, and production-ready library for all the advanced features of TFHE.

Key cryptographic concepts

The TFHE-rs library implements Zama’s variant of Fully Homomorphic Encryption over the Torus (TFHE). TFHE is based on Learning With Errors (LWE), a well-studied cryptographic primitive believed to be secure even against quantum computers.
In cryptography, a raw value is called a message (also sometimes called a cleartext), while an encoded message is called a plaintext and an encrypted plaintext is called a ciphertext.
The idea of homomorphic encryption is that you can compute on ciphertexts while not knowing messages encrypted within them. A scheme is said to be fully homomorphic, meaning any program can be evaluated with it, if at least two of the following operations are supported (
xx
is a plaintext and
E[x]E[x]
is the corresponding ciphertext):
  • homomorphic univariate function evaluation:
    f(E[x])=E[f(x)]f(E[x]) = E[f(x)]
    ​
  • homomorphic addition:
    E[x]+E[y]=E[x+y]E[x] + E[y] = E[x + y]
    ​
  • homomorphic multiplication:
    E[x]∗E[y]=E[x∗y]E[x] * E[y] = E[x * y]
    ​
Zama's variant of TFHE is fully homomorphic and deals with fixed-precision numbers as messages. It implements all needed homomorphic operations, such as addition and function evaluation via Programmable Bootstrapping. You can read more about Zama's TFHE variant in the preliminary whitepaper.
Using FHE in a Rust program with TFHE-rs consists in:
  • generating a client key and a server key using secure parameters:
    • a client key encrypts/decrypts data and must be kept secret
    • a server key is used to perform operations on encrypted data and could be public (also called an evaluation key)
  • encrypting plaintexts using the client key to produce ciphertexts
  • operating homomorphically on ciphertexts with the server key
  • decrypting the resulting ciphertexts into plaintexts using the client key
If you would like to know more about the problems that FHE solves, we suggest you review our 6 minute introduction to homomorphic encryption.