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  • Overview
    • Intro
    • Fair Math Actor
      • Fair Math Controller
      • Fair Math VM
      • Setup an Actor
    • Hello (CIFAR) world!
  • FHE Computer
    • Overview
    • Architectural Layers
      • Application Layer
      • Orchestration Layer
      • Verification Layer
      • Execution Layer
      • Data Layer
    • ISA
      • fhe
      • arith
      • tensor
      • polycircuit
    • Operating System
      • Computer State
      • Application
        • Running Applications
        • External Functions
        • Interactive APPS
      • Execution Graph and Tasks
        • Atomic and Composite Instructions
        • Instruction Unrolling
        • Task Dependencies
        • Execution Graph
      • Process
        • Process lifecycle
        • Resource Allocation and Isolation
      • Order Book
        • Matching Mechanism
        • Task Complexity
        • Instruction Complexity
        • Task re-Delegation
      • Context
        • Context Structure
      • FHE Component Repository
    • Fair Math Actors
      • Task State Monitoring
      • Execution Pairs
      • Rewards and Penalties
    • Ethereum Endpoint
    • CIFAR10 App
  • Whitepapers
    • FHE Computer
    • FHERMA
  • FHERMA
  • Resources
    • Computer CLI
    • FHERMA
    • POLYCIRCUIT (CPP)
    • OpenFHE-rs
    • Talks and Podcasts
  • Social
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On this page

FHERMA

https://fherma.io

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Last updated 5 months ago

FHERMA is a platform for Fully Homomorphic Encryption (FHE) challenges jointly developed by Fair Math and the OpenFHE teams.

The project's main goal is to develop an open-source library of FHE components. Such a library can significantly simplify application development and accelerate the adoption of FHE. The initial challenges are focused on Machine Learning and Blockchain applications.

On the platform, there are two types of challenges:

  1. Black Box: In this type of challenge, participants develop solutions according to the challenge requirements, process encrypted test data, and submit to the platform only the serialized final ciphertext. This type of challenge does not require submitting source code or any other data that reveals the details of the solution itself. The main criterion for evaluating and ranking solutions in this type of challenge is accuracy.

  2. White Box: It is impossible to evaluate the solution's performance based solely on the ciphertext. While the Black Box type is suitable for many challenges, it is crucial to obtain the most efficient solution from a performance perspective for others. For these, the White Box type is available. Participants must submit their projects' source code to the platform. The platform will compile the project and run tests to measure performance and accuracy. The main criteria for evaluating and ranking solutions in this type of challenge are performance and accuracy. Solutions uploaded to the platform are confidential and unavailable to other participants.

Challenges on are being solved using one of three languages:

Go - using

Python - using

Rust - using

C++ - using

We collect winning solutions and put them into the open-source repository . Check out the relevant to learn more about the collaborative idea behind it.

FHERMA
lattigo
openfhe-python
openfhe-rs
openfhe
Polycircuit
documentation page
IBM researchers to publish FHE challenges on the FHERMA platform - IBM BlogIBM Blog
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Talk about FHERMA and behind